Paper Digest: Recent Papers on Anomaly Detection
Paper Digest Team extracted all recent Anomaly Detection related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Anomaly Detection
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Lossy Compression for Robust Unsupervised Time-Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: A new Lossy Causal Temporal Convolutional Neural Network Autoencoder for anomaly detection is proposed in this work. |
Christopher P. Ley; Jorge F. Silva; | arxiv-cs.LG | 2022-12-05 |
| 2 | AIDA: Analytic Isolation and Distance-based Anomaly Detection Algorithm Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We combine the metrics of distance and isolation to develop the \textit{Analytic Isolation and Distance-based Anomaly (AIDA) detection algorithm}. |
Luis Antonio Souto Arias; Cornelis W. Oosterlee; Pasquale Cirillo; | arxiv-cs.LG | 2022-12-05 |
| 3 | Cross-Domain Graph Anomaly Detection Via Anomaly-aware Contrastive Alignment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we introduce a novel domain adaptation approach, namely Anomaly-aware Contrastive alignmenT (ACT), for GAD. |
Qizhou Wang; Guansong Pang; Mahsa Salehi; Wray Buntine; Christopher Leckie; | arxiv-cs.LG | 2022-12-02 |
| 4 | Attribute-based Representations for Accurate and Interpretable Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple but highly effective method that pushes the boundaries of VAD accuracy and interpretability using attribute-based representations. |
Tal Reiss; Yedid Hoshen; | arxiv-cs.CV | 2022-12-01 |
| 5 | A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a three-stage deep learning anomaly detection based network intrusion attack detection framework. |
Rahul Kale; Zhi Lu; Kar Wai Fok; Vrizlynn L. L. Thing; | arxiv-cs.CR | 2022-12-01 |
| 6 | SPADE: Semi-supervised Anomaly Detection Under Distribution Mismatch Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a canonical framework: Semi-supervised Pseudo-labeler Anomaly Detection with Ensembling (SPADE) that isn’t limited by the assumption that labeled and unlabeled data come from the same distribution. |
Jinsung Yoon; Kihyuk Sohn; Chun-Liang Li; Sercan O. Arik; Tomas Pfister; | arxiv-cs.LG | 2022-11-30 |
| 7 | Individualized Statistical Modeling of Lesions in Fundus Images for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The separation methods primarily model the diverse lesions with pixel-based independent and identical distributed (i.i.d.) properties, neglecting the individualized variations of different types of lesions and their structural properties. |
YUCHEN DU et. al. | IEEE transactions on medical imaging | 2022-11-29 |
| 8 | Supervised Anomaly Detection Via Conditional Generative Adversarial Network and Ensemble Active Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). |
Zhi Chen; Jiang Duan; Li Kang; Guoping Qiu; | IEEE transactions on pattern analysis and machine … | 2022-11-29 |
| 9 | G-CMP: Graph-enhanced Contextual Matrix Profile for Unsupervised Anomaly Detection in Sensor-based Remote Health Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel, self-supervised graph-based approach for temporal anomaly detection that works on context graphs generated from the CMP distance matrix. |
Nivedita Bijlani; Oscar Mendez Maldonado; Samaneh Kouchaki; | arxiv-cs.LG | 2022-11-29 |
| 10 | Automated Anomaly-aware 3D Segmentation of Bones and Cartilages in Knee MR Images from The Osteoarthritis Initiative Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we develop a multi-step approach using U-Net-based neural networks to initially detect anomalies (bone marrow lesions, bone cysts) in the distal femur, proximal tibia and patella from 3D magnetic resonance (MR) images of the knee in individuals with varying grades of osteoarthritis. |
BOYEONG WOO et. al. | arxiv-eess.IV | 2022-11-29 |
| 11 | Lightning Fast Video Anomaly Detection Via Adversarial Knowledge Distillation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a very fast frame-level model for anomaly detection in video, which learns to detect anomalies by distilling knowledge from multiple highly accurate object-level teacher models. |
NICOLAE-CATALIN RISTEA et. al. | arxiv-cs.CV | 2022-11-28 |
| 12 | GADMSL: Graph Anomaly Detection on Attributed Networks Via Multi-scale Substructure Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To enhance the local substructure detection ability, we propose a novel Graph Anomaly Detection framework via Multi-scale Substructure Learning (GADMSL for abbreviation). |
JINGCAN DUAN et. al. | arxiv-cs.LG | 2022-11-28 |
| 13 | A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRI Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Unsupervised methods for anomaly detection provide interesting formulations based on reconstruction or latent embedding, offering a way to observe properties related to factorization. |
Ayantika Das; Arun Palla; Keerthi Ram; Mohanasankar Sivaprakasam; | arxiv-eess.IV | 2022-11-28 |
| 14 | MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In addition, we empirically found that existing approaches that use feature magnitudes to represent the degree of anomalies typically ignore the effects of scene variations, and hence result in sub-optimal performance due to the inconsistency of feature magnitudes across scenes. To address this issue, we propose the Feature Amplification Mechanism and a Magnitude Contrastive Loss to enhance the discriminativeness of feature magnitudes for detecting anomalies. |
YINGXIAN CHEN et. al. | arxiv-cs.CV | 2022-11-28 |
| 15 | An Anomaly Detection Method for Satellites Using Monte Carlo Dropout Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a tractable approximation for BNN based on the Monte Carlo (MC) dropout method for capturing the uncertainty in the satellite telemetry time series, without sacrificing accuracy. |
Mohammad Amin Maleki Sadr; Yeying Zhu; Peng Hu; | arxiv-cs.LG | 2022-11-27 |
| 16 | MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We focus on outdoor maintenance inspection and contribute a comprehensive Maintenance Inspection Anomaly Detection (MIAD) dataset which contains more than 100K high-resolution color images in various outdoor industrial scenarios. |
TIANPENG BAO et. al. | arxiv-cs.CV | 2022-11-25 |
| 17 | A Deep Learning Anomaly Detection Method in Textual Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose using deep learning and transformer architectures combined with classical machine learning algorithms to detect and identify text anomalies in texts. |
Amir Jafari; | arxiv-cs.CL | 2022-11-25 |
| 18 | Towards Interpretable Anomaly Detection Via Invariant Rule Mining Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we pursue highly interpretable anomaly detection via invariant rule mining. |
Cheng Feng; Pingge Hu; | arxiv-cs.LG | 2022-11-24 |
| 19 | Meta-Learning for Automated Selection of Anomaly Detectors for Semi-Supervised Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate automated machine learning for anomaly detectors, we propose to employ meta-learning to predict MCC scores based on metrics that can be computed with normal data only. |
David Schubert; Pritha Gupta; Marcel Wever; | arxiv-cs.LG | 2022-11-24 |
| 20 | Detecting Anomalies Using Generative Adversarial Networks on Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel Generative Adversarial Network (GAN) based model for anomaly detection. |
Rushikesh Zawar; Krupa Bhayani; Neelanjan Bhowmik; Kamlesh Tiwari; Dhiraj Sangwan; | arxiv-cs.CV | 2022-11-24 |
| 21 | Generalizable Industrial Visual Anomaly Detection with Self-Induction Vision Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Moreover, existing studies follow the individual learning fashion where the detection models are only capable of one category of the product while the generalizable detection for multiple categories has not been explored. To tackle the above limitations, we proposed a self-induction vision Transformer(SIVT) for unsupervised generalizable multi-category industrial visual anomaly detection and localization. |
Haiming Yao; Wenyong Yu; | arxiv-cs.CV | 2022-11-22 |
| 22 | Image Anomaly Detection and Localization with Position and Neighborhood Information Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To use the information, in this paper, the normal distribution is estimated with conditional probability given neighborhood features, which is modeled with a multi-layer perceptron network. |
Jaehyeok Bae; Jae-Han Lee; Seyun Kim; | arxiv-cs.CV | 2022-11-22 |
| 23 | U-Flow: A U-shaped Normalizing Flow for Anomaly Detection with Unsupervised Threshold Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a non-contrastive method for anomaly detection and segmentation in images, that benefits both from a modern machine learning approach and a more classic statistical detection theory. |
Matías Tailanian; Álvaro Pardo; Pablo Musé; | arxiv-cs.CV | 2022-11-22 |
| 24 | FRE: A Fast Method For Anomaly Detection And Segmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a fast and principled approach for solving the visual anomaly detection and segmentation problem. |
Ibrahima Ndiour; Nilesh Ahuja; Utku Genc; Omesh Tickoo; | arxiv-cs.CV | 2022-11-22 |
| 25 | MGADN: A Multi-task Graph Anomaly Detection Network for Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach uses GAT, which is originated from graph neural network, to obtain connection between sensors. |
Weixuan Xiong; Xiaochen Sun; | arxiv-cs.LG | 2022-11-22 |
| 26 | Immersion and Invariance-based Coding for Privacy in Remote Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a framework for the design of coding mechanisms that allow remotely operating anomaly detectors in a privacy-preserving manner. |
Haleh Hayati; Nathan van de Wouw; Carlos Murguia; | arxiv-cs.CR | 2022-11-21 |
| 27 | A Deep Learning Approach to Detect Anomalies in An Electric Power Steering System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a deep learning approach that consists of a two-stage process using an autoencoder and long short-term memory (LSTM) to detect anomalies in EPS sensor data. |
Lawal Wale Alabe; Kimleang Kea; Youngsun Han; Young Jae Min; Taekyung Kim; | Sensors (Basel, Switzerland) | 2022-11-20 |
| 28 | Normalizing Flows for Human Pose Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our model works directly on human pose graph sequences and is exceptionally lightweight ($\sim1K$ parameters), capable of running on any machine able to run the pose estimation with negligible additional resources. We leverage the highly compact pose representation in a normalizing flows framework, which we extend to tackle the unique characteristics of spatio-temporal pose data and show its advantages in this use case. |
Or Hirschorn; Shai Avidan; | arxiv-cs.CV | 2022-11-20 |
| 29 | Reference-Based Autoencoder for Surface Defect Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Furthermore, existing reconstruction-based methods do not have a strong ability to convert the defect feature to the normal feature. To address these challenges, we propose a novel unsupervised reference-based autoencoder (RB-AE) to accurately inspect a variety of textured defects. |
Wei Luo; Haiming Yao; Wenyong Yu; Xue Wang; | arxiv-cs.CV | 2022-11-18 |
| 30 | Deep Graph Level Anomaly Detection with Contrastive Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We aim to design a new graph level anomaly evaluation way, which first utilizes the contrastive learning strategy to enhance different level representations of normal graphs from node and graph levels by a graph convolution autoencoder with perturbed graph encoder. |
XUEXIONG LUO et. al. | Scientific reports | 2022-11-18 |
| 31 | Pedestrian Spatio-Temporal Information Fusion For Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Aiming at the problem that the current video anomaly detection cannot fully use the temporal information and ignore the diversity of normal behavior, an anomaly detection method is proposed to integrate the spatiotemporal information of pedestrians. |
Chao Hu; Liqiang Zhu; | arxiv-cs.CV | 2022-11-18 |
| 32 | Self-Supervision-Augmented Deep Autoencoder for Unsupervised Visual Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, this hypothesis cannot be always tenable since the deep AE usually captures the low-level shared features between normal and abnormal data, which leads to similar reconstruction errors for them. To tackle this problem, we propose a self-supervised representation-augmented deep AE for unsupervised VAD, which can enlarge the gap of anomaly scores between normal and abnormal samples by introducing autoencoding transformation (AT). |
CHAO HUANG et. al. | IEEE transactions on cybernetics | 2022-11-18 |
| 33 | Rare Yet Popular: Evidence and Implications from Labeled Datasets for Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Anomaly detection research works generally propose algorithms or end-to-end systems that are designed to automatically discover outliers in a dataset or a stream. |
Jose Manuel Navarro; Alexis Huet; Dario Rossi; | arxiv-cs.NI | 2022-11-18 |
| 34 | Spatial-contextual Variational Autoencoder with Attention Correction for Anomaly Detection in Retinal OCT Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection refers to leveraging only normal data to train a model for identifying unseen abnormal cases, which is extensively studied in various fields. Most previous … |
XUEYING ZHOU et. al. | Computers in biology and medicine | 2022-11-17 |
| 35 | Anomaly Detection Via Multi-Scale Contrasted Memory Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Moreover, there currently does not exist a unified framework efficiently covering both one-class and unbalanced learnings. In the light of these limitations, we introduce a new two-stage anomaly detector which memorizes during training multi-scale normal prototypes to compute an anomaly deviation score. |
Loic Jezequel; Ngoc-Son Vu; Jean Beaudet; Aymeric Histace; | arxiv-cs.CV | 2022-11-16 |
| 36 | Are We Certain It’s Anomalous? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we propose the novel use of Hyperbolic uncertainty for Anomaly Detection (HypAD). |
ALESSANDRO FLABOREA et. al. | arxiv-cs.LG | 2022-11-16 |
| 37 | LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an anomaly detection model that combines the strong statistical foundation of density-estimation-based anomaly detection methods with the representation-learning ability of deep-learning models. |
Joseph Gallego-Mejia; Oscar Bustos-Brinez; Fabio A. González; | arxiv-cs.LG | 2022-11-15 |
| 38 | FAPM: Fast Adaptive Patch Memory for Real-time Industrial Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, such approaches do not consider the inference speed, which is as important as accuracy in real-world applications. To relieve this issue, we propose a method called fast adaptive patch memory (FAPM) for real-time industrial anomaly detection. |
Donghyeong Kim; Chaewon Park; Suhwan Cho; Sangyoun Lee; | arxiv-cs.CV | 2022-11-14 |
| 39 | Deep Learning for Time Series Anomaly Detection: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Aside from describing the basic anomaly detection technique for each category, the advantages and limitations are also discussed. |
Zahra Zamanzadeh Darban; Geoffrey I. Webb; Shirui Pan; Charu C. Aggarwal; Mahsa Salehi; | arxiv-cs.LG | 2022-11-09 |
| 40 | Evaluation of Color Anomaly Detection in Multispectral Images For Synthetic Aperture Sensing Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this article, we evaluate unsupervised anomaly detection methods in multispectral images obtained with a wavelength-independent synthetic aperture sensing technique, called Airborne Optical Sectioning (AOS). |
Francis Seits; Indrajit Kurmi; Oliver Bimber; | arxiv-cs.CV | 2022-11-08 |
| 41 | Quantum-probabilistic Hamiltonian Learning for Generative Modelling & Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This study investigates the possibility of learning and utilising a system’s Hamiltonian and its variational thermal state estimation for data analysis techniques. For this purpose, we employ the method of Quantum Hamiltonian-Based Models for the generative modelling of simulated Large Hadron Collider data and demonstrate the representability of such data as a mixed state. |
Jack Y. Araz; Michael Spannowsky; | arxiv-quant-ph | 2022-11-07 |
| 42 | Perturbation Learning Based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a simple yet effective method for anomaly detection. |
Jinyu Cai; Jicong Fan; | nips | 2022-11-06 |
| 43 | ADBench: Anomaly Detection Benchmark Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and (iii) noisy and corrupted data? In this work, we answer these key questions by conducting (to our best knowledge) the most comprehensive anomaly detection benchmark with 30 algorithms on 57 benchmark datasets, named ADBench. |
Songqiao Han; Xiyang Hu; Hailiang Huang; Minqi Jiang; Yue Zhao; | nips | 2022-11-06 |
| 44 | SoftCore: Unsupervised Anomaly Detection with Noisy Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper considers label-level noise in sensory anomaly detection for the first time. To solve this problem, we proposed a memory-based unsupervised AD method, SoftCore, which efficiently denoises the data at the patch level. |
XI JIANG et. al. | nips | 2022-11-06 |
| 45 | DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper present DGraph, a real-world dynamic graph in the finance domain. |
XUANWEN HUANG et. al. | nips | 2022-11-06 |
| 46 | Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a dual-discriminative graph neural network for graph-level anomaly detection, namely iGAD. |
GE ZHANG et. al. | nips | 2022-11-06 |
| 47 | A Unified Model for Multi-class Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present UniAD that accomplishes anomaly detection for multiple classes with a unified framework. |
ZHIYUAN YOU et. al. | nips | 2022-11-06 |
| 48 | Deep Reinforcement Learning for The Detection of Abnormal Data in Smart Meters Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work uses the greedy policy algorithm to find the action of the maximum value of based on the -learning method to obtain the optimal calculation policy. |
SHUXIAN SUN et. al. | Sensors (Basel, Switzerland) | 2022-11-06 |
| 49 | DA-LSTM-VAE: Dual-Stage Attention-Based LSTM-VAE for KPI Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: To ensure the normal operation of the system, the enterprise’s operations engineer will monitor the system through the KPI (key performance indicator). For example, web page … |
Yun Zhao; Xiuguo Zhang; Zijing Shang; Zhiying Cao; | Entropy (Basel, Switzerland) | 2022-11-05 |
| 50 | DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use isolation tree-based unsupervised clustering to partition the deep feature space of the video segments. |
Kamalakar Thakare; Yash Raghuwanshi; Debi Prosad Dogra; Heeseung Choi; Ig-Jae Kim; | arxiv-cs.CV | 2022-11-02 |
| 51 | HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel semi-supervised anomaly detection framework based on a heterogeneous feature network (HFN) for MTS, learning heterogeneous structure information from a mass of unlabeled time-series data to improve the accuracy of anomaly detection, and using attention coefficient to provide an explanation for the detected anomalies. |
Jun Zhan; Chengkun Wu; Canqun Yang; Qiucheng Miao; Xiandong Ma; | arxiv-cs.LG | 2022-11-01 |
| 52 | Siamese Transition Masked Autoencoders As Uniform Unsupervised Visual Anomaly Detector Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel hybrid framework termed Siamese Transition Masked Autoencoders(ST-MAE) to handle various visual anomaly detection tasks uniformly via deep feature transition. |
Haiming Yao; Xue Wang; Wenyong Yu; | arxiv-cs.CV | 2022-11-01 |
| 53 | Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We apply our model to two examples of galaxy morphology classification tasks with anomaly detection: 1) classifying spiral and elliptical galaxies with detection of merging galaxies (three classes including one unknown anomaly class); 2) a more granular problem where the classes describe more detailed morphological properties of galaxies, with the detection of gravitational lenses (ten classes including one unknown anomaly class). |
ALEKSANDRA ĆIPRIJANOVIĆ et. al. | arxiv-astro-ph.GA | 2022-11-01 |
| 54 | Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few Normal Samples Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, drawing inspiration from the knowledge transfer ability of teacher-student architecture and the impressive feature extraction capability of recent neural networks, we design a teacher-student structured model for 3D anomaly detection. |
Jianjian Qin; Chunzhi Gu; Jun Yu; Chao Zhang; | arxiv-cs.CV | 2022-10-31 |
| 55 | TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose a Time-Frequency analysis based time series Anomaly Detection model, or TFAD for short, to exploit both time and frequency domains for performance improvement. |
Chaoli Zhang; Tian Zhou; Qingsong Wen; Liang Sun; | cikm | 2022-10-29 |
| 56 | Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel and powerful framework, dubbed as SLA2P, for unsupervised anomaly detection. |
YIZHOU WANG et. al. | cikm | 2022-10-29 |
| 57 | Towards An Awareness of Time Series Anomaly Detection Models’ Adversarial Vulnerability Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: The overarching goal of this research is to raise awareness towards the adversarial vulnerabilities of time series anomaly detectors. |
Shahroz Tariq; Binh M. Le; Simon S. Woo; | cikm | 2022-10-29 |
| 58 | Learning Hypersphere for Few-shot Anomaly Detection on Attributed Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a latent hazard in existing systems, anomalies can be transformed into important instruction information once we detect them, e.g., computer network admins can react to the leakage of sensitive data if network traffic anomalies are identified. Extensive research in anomaly detection on attributed networks has proposed various techniques, which do improve the quality of data in networks, while they rarely cope with the few-shot anomaly detection problem. |
QIUYU GUO et. al. | cikm | 2022-10-29 |
| 59 | MARINA: An MLP-Attention Model for Multivariate Time-Series Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, in this paper, we propose a Multi-layer perceptron (<u>M</u>LP)-<u>a</u>ttention based multivariate time-se<u>ri</u>es a<u>na</u>lysis model MARINA. |
Jiandong Xie; Yue Cui; Feiteng Huang; Chao Liu; Kai Zheng; | cikm | 2022-10-29 |
| 60 | Quantum Variational Rewinding for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: With the advent of newly accessible quantum processing units (QPUs), exploring a quantum approach to TAD is now relevant and is the topic of this work. |
JACK S. BAKER et. al. | arxiv-quant-ph | 2022-10-28 |
| 61 | Learning to Detect Interesting Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Anomaly detection algorithms are typically applied to static, unchanging, data features hand-crafted by the user. |
Alireza Vafaei Sadr; Bruce A. Bassett; Emmanuel Sekyi; | arxiv-cs.LG | 2022-10-28 |
| 62 | Deep Learning-Based Anomaly Detection in Synthetic Aperture Radar Imaging Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed to investigate unsupervised anomaly detection in Synthetic Aperture Radar (SAR) images. |
Max Muzeau; Chengfang Ren; Sébastien Angelliaume; Mihai Datcu; Jean-Philippe Ovarlez; | arxiv-cs.CV | 2022-10-28 |
| 63 | Joint Sub-component Level Segmentation and Classification for Anomaly Detection Within Dual-Energy X-Ray Security Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The automatic detection of anomaly, which is concealed within cluttered and complex electronics/electrical items, using 2D X-ray imagery is of primary interest in recent years. We address this task by introducing joint object sub-component level segmentation and classification strategy using deep Convolution Neural Network architecture. |
Neelanjan Bhowmik; Toby P. Breckon; | arxiv-cs.CV | 2022-10-28 |
| 64 | Online Multivariate Anomaly Detection and Localization for High-Dimensional Settings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: This paper considers the real-time detection of abrupt and persistent anomalies in high-dimensional data streams. The goal is to detect anomalies quickly and accurately so that … |
Mahsa Mozaffari; Keval Doshi; Yasin Yilmaz; | Sensors (Basel, Switzerland) | 2022-10-28 |
| 65 | SDN-Defend: A Lightweight Online Attack Detection and Mitigation System for DDoS Attacks in SDN Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the development of Software Defined Networking (SDN), its security is becoming increasingly important. Since SDN has the characteristics of centralized management and … |
Jin Wang; Liping Wang; | Sensors (Basel, Switzerland) | 2022-10-28 |
| 66 | Local Anomaly Detection for Multivariate Time Series By Temporal Dependency Based on Poisson Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Methodologically, we propose a unified learning framework to characterize the residuals and their coherence with the temporal aspect of the whole multivariate time series. |
Seif-Eddine Benkabou; Khalid Benabdeslem; Vivien Kraus; Kilian Bourhis; Bruno Canitia; | IEEE transactions on neural networks and learning systems | 2022-10-27 |
| 67 | AUD-Net: A Unified Deep Detector for Multiple Hyperspectral Image Anomaly Detection Via Relation and Few-Shot Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article addresses the problem of the building an out-of-the-box deep detector, motivated by the need to perform anomaly detection across multiple hyperspectral images (HSIs) without repeated training. |
Ning Huyan; Xiangrong Zhang; Dou Quan; Jocelyn Chanussot; Licheng Jiao; | IEEE transactions on neural networks and learning systems | 2022-10-27 |
| 68 | Weakly Supervised Discriminative Learning With Spectral Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article proposes a weakly supervised discriminative learning with a spectral constrained generative adversarial network (GAN) for hyperspectral anomaly detection (HAD), called weaklyAD. |
Tao Jiang; Weiying Xie; Yunsong Li; Jie Lei; Qian Du; | IEEE transactions on neural networks and learning systems | 2022-10-27 |
| 69 | Feature Generation and Contribution Comparison for Electronic Fraud Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Past literature categorizes these features into recency, frequency, monetary, and anomaly detection features. We use various machine learning algorithms to examine the performance of features in these four categories with real transaction data; we compare them with the performance of our feature generation guideline based on the statistical perspectives and characteristics of (non)-fraudulent accounts. |
Yen-Wu Ti; Yu-Yen Hsin; Tian-Shyr Dai; Ming-Chuan Huang; Liang-Chih Liu; | Scientific reports | 2022-10-27 |
| 70 | AD-DMKDE: Anomaly Detection Through Density Matrices and Fourier Features Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel density estimation method for anomaly detection using density matrices (a powerful mathematical formalism from quantum mechanics) and Fourier features. |
Oscar Bustos-Brinez; Joseph Gallego-Mejia; Fabio A. González; | arxiv-cs.LG | 2022-10-26 |
| 71 | Resonant Anomaly Detection Without Background Sculpting Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new technique named Latent CATHODE (LaCATHODE) for performing enhanced bump hunts, a type of resonant anomaly search that combines conventional one-dimensional bump hunts with a model-agnostic anomaly score in an auxiliary feature space where potential signals could also be localized. |
Anna Hallin; Gregor Kasieczka; Tobias Quadfasel; David Shih; Manuel Sommerhalder; | arxiv-physics.data-an | 2022-10-26 |
| 72 | Interpretable Anomaly Detection in Event Sequences Via Sequence Matching and Visual Comparison Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose a visual analytic approach for detecting anomalous sequences in an event sequence dataset via an unsupervised anomaly detection algorithm based on Variational AutoEncoders. |
SHUNAN GUO et. al. | IEEE transactions on visualization and computer graphics | 2022-10-26 |
| 73 | Research on DUAL-ADGAN Model for Anomaly Detection Method in Time-Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, there are problems of unstable generator training, missed detection of anomalous data, and inconsistency between the discriminator’s discriminant and the anomaly detection target in GAN networks. Aiming at the above problems, the paper proposes a DUAL-ADGAN (Dual Anomaly Detection Generative Adversarial Networks) model for the detection of anomalous data in time series. |
Xingyu Gong; Xin Wang; Na Li; | Computational intelligence and neuroscience | 2022-10-26 |
| 74 | Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present datasets that are typically used for benchmarking, produce a taxonomy of the developed algorithms, and discuss and compare their performances. |
Md. Haidar Sharif; Lei Jiao; Christian W. Omlin; | arxiv-cs.CV | 2022-10-25 |
| 75 | Anomaly Detection in Industrial IoT Using Distributional Reinforcement Learning and Generative Adversarial Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is one of the biggest issues of security in the Industrial Internet of Things (IIoT) due to the increase in cyber attack dangers for distributed devices and … |
Hafsa Benaddi; Mohammed Jouhari; Khalil Ibrahimi; Jalel Ben Othman; El Mehdi Amhoud; | Sensors (Basel, Switzerland) | 2022-10-22 |
| 76 | Ordinal Regression for Direction-Related Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, to detect the aforementioned direction-related anomalies, we propose an ordinal regression algorithm for direction-related anomaly detection (ORAD). |
Jiankai Tu; Huan Liu; Chunguang Li; | IEEE transactions on neural networks and learning systems | 2022-10-21 |
| 77 | Improving The Anomaly Detection in GPR Images By Fine-Tuning CNNs with Synthetic Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a novel method is proposed to improve the subsurface anomaly detection from GPR B-scan images. |
Xiren Zhou; Shikang Liu; Ao Chen; Yizhan Fan; Huanhuan Chen; | arxiv-cs.CV | 2022-10-21 |
| 78 | Frequency of Interest-based Noise Attenuation Method to Improve Anomaly Detection Performance Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Accurately extracting driving events is the way to maximize computational efficiency and anomaly detection performance in the tire frictional nose-based anomaly detection task. This study proposes a concise and highly useful method for improving the precision of the event extraction that is hindered by extra noise such as wind noise, which is difficult to characterize clearly due to its randomness. |
YeongHyeon Park; Myung Jin Kim; Won Seok Park; | arxiv-cs.LG | 2022-10-20 |
| 79 | Anomaly Detection and Correction of Optimizing Autonomous Systems With Inverse Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article considers autonomous systems whose behaviors seek to optimize an objective function. |
BOSEN LIAN et. al. | IEEE transactions on cybernetics | 2022-10-20 |
| 80 | Self-Supervised Sparse Representation for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To establish a unified approach to solving the two VAD settings, we introduce a self-supervised sparse representation (S3R) framework that models the concept of anomaly at feature level by exploring the synergy between dictionary-based representation and self-supervised learning. |
Jhih-Ciang Wu; He-Yen Hsieh; Ding-Jie Chen; Chiou-Shann Fuh; Tyng-Luh Liu; | eccv | 2022-10-19 |
| 81 | Anomaly Detection Requires Better Representations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection seeks to identify unusual phenomena, a central task in science and industry. The task is inherently unsupervised as anomalies are unexpected and unknown during … |
Tal Reiss; Niv Cohen; Eliahu Horwitz; Ron Abutbul; Yedid Hoshen; | arxiv-cs.LG | 2022-10-19 |
| 82 | Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To overcome these drawbacks, we introduce DLAN-AC, a Dynamic Local Aggregation Network with Adaptive Clusterer, for anomaly detection. |
Zhiwei Yang; Peng Wu; Jing Liu; Xiaotao Liu; | eccv | 2022-10-19 |
| 83 | Registration Based Few-Shot Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper considers few-shot anomaly detection (FSAD), a practical yet under-studied setting for anomaly detection (AD), where only a limited number of normal images are provided for each category at training. |
CHAOQIN HUANG et. al. | eccv | 2022-10-19 |
| 84 | DSR – A Dual Subspace Re-Projection Network for Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an architecture based on quantized feature space representation with dual decoders, DSR, that avoids the image-level anomaly synthesis requirement. |
Vitjan Zavrtanik; Matej Kristan; Danijel Sko?aj; | eccv | 2022-10-19 |
| 85 | DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We therefore design a novel hybrid algorithm based on reinterpreting discriminative logits as a logarithm of the unnormalized joint distribution $\hat{p}(\mathbf{x},\mathbf{y})$ |
Matej Grci?; Petra Bevandi?; Siniša Šegvi?; | eccv | 2022-10-19 |
| 86 | Estimating The Contamination Factor’s Distribution in Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Unfortunately, there are no good methods for estimating the contamination factor itself. We address this need from a Bayesian perspective, introducing a method for estimating the posterior distribution of the contamination factor of a given unlabeled dataset. |
Lorenzo Perini; Paul Buerkner; Arto Klami; | arxiv-cs.LG | 2022-10-19 |
| 87 | SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we present a new dataset as well as a new self-supervised learning method for ImageNet pre-training to improve anomaly detection and segmentation in 1-class and 2-class 5/10/high-shot training setups. |
Yang Zou; Jongheon Jeong; Latha Pemula; Dongqing Zhang; Onkar Dabeer; | eccv | 2022-10-19 |
| 88 | Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: However, when contaminated with unlabeled abnormal samples in training set under semi-supervised settings, current contrastive-based methods generally 1) ignore the comprehensive relation between training data, leading to suboptimal performance, and 2) require fine-tuning, resulting in low efficiency. To address the above two issues, in this paper, we propose a novel hierarchical semi-supervised contrastive learning (HSCL) framework, for contamination-resistant anomaly detection. |
Gaoang Wang; Yibing Zhan; Xinchao Wang; Mingli Song; Klara Nahrstedt; | eccv | 2022-10-19 |
| 89 | Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We introduce a simple and intuitive self-supervision task, Natural Synthetic Anomalies (NSA), for training an end-to-end model for anomaly detection and localization using only normal training data. |
ter Hannah M. Schlü Jeremy Tan; Benjamin Hou; Bernhard Kainz; | eccv | 2022-10-19 |
| 90 | DAGAD: Data Augmentation for Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Graph anomaly detection in this paper aims to distinguish abnormal nodes that behave differently from the benign ones accounting for the majority of graph-structured instances. |
FANZHEN LIU et. al. | arxiv-cs.LG | 2022-10-18 |
| 91 | Spatio-Temporal-based Context Fusion for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, a video anomaly detection algorithm based on target spatio-temporal context fusion is proposed. |
Chao Hu; Weibin Qiu; Weijie Wu; Liqiang Zhu; | arxiv-cs.CV | 2022-10-18 |
| 92 | N-pad : Neighboring Pixel-based Industrial Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To employ the relative positional information of each pixel, we present \textit{\textbf{N-pad}}, a novel method for anomaly detection and segmentation in a one-class learning setting that includes the neighborhood of the target pixel for model training and evaluation. |
JunKyu Jang; Eugene Hwang; Sung-Hyuk Park; | arxiv-cs.CV | 2022-10-17 |
| 93 | Graph Anomaly Detection with Unsupervised GNNs Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This work aims to fill two gaps in the literature: We (1) design GLAM, an end-to-end graph-level anomaly detection model based on GNNs, and (2) focus on unsupervised model selection, which is notoriously hard due to lack of any labels, yet especially critical for deep NN based models with a long list of hyper-parameters. |
Lingxiao Zhao; Saurabh Sawlani; Arvind Srinivasan; Leman Akoglu; | arxiv-cs.LG | 2022-10-17 |
| 94 | Tegdet: An Extensible Python Library for Anomaly Detection Using Time-Evolving Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a new Python library for anomaly detection in unsupervised learning approaches. |
Simona Bernardi; José Merseguer; Raúl Javierre; | arxiv-cs.LG | 2022-10-17 |
| 95 | Occluded Object Detection and Exposure in Cluttered Environments with Automated Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Cluttered environments with partial object occlusions pose significant challenges to robot manipulation. In settings composed of one dominant object type and various undesirable … |
Nathaniel Hanson; Gary Lvov; Taşkın Padir; | Frontiers in robotics and AI | 2022-10-14 |
| 96 | Reconstructed Student-Teacher and Discriminative Networks for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, a powerful anomaly detection method is proposed based on student-teacher feature pyramid matching (STPM), which consists of a student and teacher network. |
Shinji Yamada; Satoshi Kamiya; Kazuhiro Hotta; | arxiv-cs.CV | 2022-10-14 |
| 97 | VHetNets for AI and AI for VHetNets: An Anomaly Detection Case Study for Ubiquitous IoT Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we develop an AI-native VHetNets-enabled framework to provide the anomaly detection service for ubiquitous IoT, whose implementation is assisted by intelligent network management functionalities. |
WEILI WANG et. al. | arxiv-cs.NI | 2022-10-14 |
| 98 | Multi-Task Learning Based Video Anomaly Detection with Attention Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the aforementioned shortcomings, we propose a novel multi-task learning based method that combines complementary proxy tasks to better consider the motion and appearance features. |
Mohammad Baradaran; Robert Bergevin; | arxiv-cs.CV | 2022-10-14 |
| 99 | Learning Image Representations for Anomaly Detection: Application to Discovery of Histological Alterations in Drug Development Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present a system for anomaly detection in histopathological images. |
Igor Zingman; Birgit Stierstorfer; Charlotte Lempp; Fabian Heinemann; | arxiv-cs.CV | 2022-10-14 |
| 100 | Asymmetric Student-Teacher Networks for Industrial Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work discovers previously unknown problems of student-teacher approaches for AD and proposes a solution, where two neural networks are trained to produce the same output for the defect-free training examples. |
Marco Rudolph; Tom Wehrbein; Bodo Rosenhahn; Bastian Wandt; | arxiv-cs.LG | 2022-10-14 |
| 101 | Anomaly Detection in Dynamic Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we introduce \textit{oddnet}, a feature-based network anomaly detection method that uses time series methods to model temporal dependencies. |
Sevvandi Kandanaarachchi; Rob J Hyndman; | arxiv-cs.SI | 2022-10-13 |
| 102 | A Survey on Explainable Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a taxonomy based on the main aspects that characterize each explainable anomaly detection technique, aiming to help practitioners and researchers find the explainable anomaly detection method that best suits their needs. |
Zhong Li; Yuxuan Zhu; Matthijs van Leeuwen; | arxiv-cs.LG | 2022-10-13 |
| 103 | Overlooked Video Classification in Weakly Supervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we study explicitly the power of video classification supervision using a BERT or LSTM. |
Weijun Tan; Qi Yao; Jingfeng Liu; | arxiv-cs.CV | 2022-10-12 |
| 104 | Anomaly Detection Via Federated Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel anomaly detector via federated learning to detect malicious network activity on a client’s server. |
MARC VUCOVICH et. al. | arxiv-cs.LG | 2022-10-12 |
| 105 | Anomaly Detection Using Generative Models and Sum-Product Networks in Mammography Scans Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel combination of generative models and a probabilistic graphical model. |
MARC DIETRICHSTEIN et. al. | arxiv-cs.CV | 2022-10-12 |
| 106 | Ship Classification and Anomaly Detection Based on Spaceborne AIS Data Considering Behavior Characteristics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the establishment of satellite constellations equipped with ship automatic identification system (AIS) receivers, the amount of AIS data is continuously increasing, and AIS … |
Zhenguo Yan; Xin Song; Hanyang Zhong; Lei Yang; Yitao Wang; | Sensors (Basel, Switzerland) | 2022-10-11 |
| 107 | The Eyecandies Dataset for Unsupervised Multimodal Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present Eyecandies, a novel synthetic dataset for unsupervised anomaly detection and localization. |
Luca Bonfiglioli; Marco Toschi; Davide Silvestri; Nicola Fioraio; Daniele De Gregorio; | arxiv-cs.CV | 2022-10-10 |
| 108 | InQMAD: Incremental Quantum Measurement Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present a new incremental anomaly detection method that performs continuous density estimation based on random Fourier features and the mechanism of quantum measurements and density matrices that can be viewed as an exponential moving average density. |
Joseph Gallego-Mejia; Oscar Bustos-Brinez; Fabio Gonzalez; | arxiv-cs.LG | 2022-10-10 |
| 109 | Dual-distribution Discrepancy with Self-supervised Refinement for Anomaly Detection in Medical Images Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: A large number of readily available unlabeled images containing anomalies are thus ignored in the training phase, restricting their performance. To solve this problem, we propose the Dual-distribution Discrepancy for Anomaly Detection (DDAD), utilizing both known normal images and unlabeled images. |
Yu Cai; Hao Chen; Xin Yang; Yu Zhou; Kwang-Ting Cheng; | arxiv-cs.CV | 2022-10-09 |
| 110 | Fine-grained Anomaly Detection in Sequential Data Via Counterfactual Explanations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel framework called CFDet for fine-grained anomalous entry detection. |
He Cheng; Depeng Xu; Shuhan Yuan; Xintao Wu; | arxiv-cs.LG | 2022-10-08 |
| 111 | Anomaly Detection Using Data Depth: Multivariate Case Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, data depth is studied as an efficient anomaly detection tool, assigning abnormality labels to observations with lower depth values, in a multivariate setting. |
Pavlo Mozharovskyi; | arxiv-stat.ML | 2022-10-06 |
| 112 | Env-Aware Anomaly Detection: Ignore Style Changes, Stay True to Content! Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a formalization and benchmark for the unsupervised anomaly detection task in the distribution-shift scenario. |
Stefan Smeu; Elena Burceanu; Andrei Liviu Nicolicioiu; Emanuela Haller; | arxiv-cs.CV | 2022-10-06 |
| 113 | Null Hypothesis Test for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We extend the use of Classification Without Labels for anomaly detection with a hypothesis test designed to exclude the background-only hypothesis. |
Jernej F. Kamenik; Manuel Szewc; | arxiv-hep-ph | 2022-10-05 |
| 114 | Improved Anomaly Detection By Using The Attention-Based Isolation Forest Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: The Huber’s contamination model is proposed to be used for defining the attention weights and their parameters. |
Lev V. Utkin; Andrey Y. Ageev; Andrei V. Konstantinov; | arxiv-cs.LG | 2022-10-05 |
| 115 | Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, anomaly detection is considered for hyperspectral imagery in the Gaussian background with an unknown covariance matrix. |
JUN LIU et. al. | IEEE transactions on neural networks and learning systems | 2022-10-05 |
| 116 | Detecting Anomaly Event in Video Based on Generative Adversarial Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Different from the main research trend, this paper focuses on combining ensemble learning and deep neural networks and proposes an approach based on ensemble generative adversarial network (GAN). |
Zhaoxian Zhang; | Computational intelligence and neuroscience | 2022-10-05 |
| 117 | OneFlow: One-Class Flow for Anomaly Detection Based on A Minimal Volume Region Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose OneFlow – a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. |
LUKASZ MAZIARKA et. al. | IEEE transactions on pattern analysis and machine … | 2022-10-04 |
| 118 | AnoML-IoT: An End to End Re-configurable Multi-protocol Anomaly Detection Pipeline for Internet of Things Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we present AnoML which is an end-to-end data science pipeline that allows the integration of multiple wireless communication protocols, anomaly detection algorithms, deployment to the edge, fog, and cloud platforms with minimal user interaction. |
Hakan Kayan; Yasar Majib; Wael Alsafery; Mahmoud Barhamgi; Charith Perera; | arxiv-cs.NI | 2022-10-04 |
| 119 | Future Frame Prediction Network for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to formulate the video anomaly detection problem within a regime of video prediction. |
Weixin Luo; Wen Liu; Dongze Lian; Shenghua Gao; | IEEE transactions on pattern analysis and machine … | 2022-10-04 |
| 120 | Multiple Instance Learning for Detecting Anomalies Over Sequential Real-World Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an MIL-based formulation and various algorithmic instantiations of this framework based on different design decisions for key components of the framework. |
Parastoo Kamranfar; David Lattanzi; Amarda Shehu; Daniel Barbará; | arxiv-cs.LG | 2022-10-04 |
| 121 | CADet: Fully Self-Supervised Anomaly Detection With Contrastive Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by this approach, we introduce CADet (Contrastive Anomaly Detection), a method based on image augmentations to perform anomaly detection on single samples. |
Charles Guille-Escuret; Pau Rodriguez; David Vazquez; Ioannis Mitliagkas; Joao Monteiro; | arxiv-cs.LG | 2022-10-04 |
| 122 | Unsupervised Model Selection for Time-series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We formulate metric combination with multiple imperfect surrogate metrics as a robust rank aggregation problem. |
Mononito Goswami; Cristian Challu; Laurent Callot; Lenon Minorics; Andrey Kan; | arxiv-cs.LG | 2022-10-03 |
| 123 | Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To this end, we propose a novel self-supervised deep learning framework CAAD for anomaly detection in wireless communication systems. |
Gopikrishna Rathinavel; Nikhil Muralidhar; Timothy O’Shea; Naren Ramakrishnan; | arxiv-cs.CR | 2022-10-01 |
| 124 | Image-Based Detection of Modifications in Gas Pump PCBs with Deep Convolutional Autoencoders Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce an approach for detecting modifications in assembled printed circuit boards based on photographs taken without tight control over perspective and illumination conditions. |
Diulhio Candido de Oliveira; Bogdan Tomoyuki Nassu; Marco Aurelio Wehrmeister; | arxiv-cs.CV | 2022-09-30 |
| 125 | Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we review the recent advances made in detecting graph anomalies using GNN models. |
Hwan Kim; Byung Suk Lee; Won-Yong Shin; Sungsu Lim; | arxiv-cs.LG | 2022-09-29 |
| 126 | Anomaly Detection Optimization Using Big Data and Deep Learning to Reduce False-positive Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this research paper, we propose applying deep model instead of traditional models because it has more ability to generalize. |
Khloud Al Jallad; Mohamad Aljnidi; Mohammad Said Desouki; | arxiv-cs.AI | 2022-09-28 |
| 127 | MTEDS: Multivariant Time Series-Based Encoder-Decoder System for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Intrusion detection systems examine the computer or network for potential security vulnerabilities. Time series data is real-valued. The nature of the data influences the type of … |
A Reyana; Sandeep Kautish; I S Yahia; Ali Wagdy Mohamed; | Computational intelligence and neuroscience | 2022-09-28 |
| 128 | Spatio-Temporal Relation Learning for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Spatial-Temporal Relation Learning (STRL) framework to tackle the video anomaly detection task. |
Hui Lv; Zhen Cui; Biao Wang; Jian Yang; | arxiv-cs.CV | 2022-09-26 |
| 129 | Enhancing Claim Classification with Feature Extraction from Anomaly-Detection-Derived Routine and Peculiarity Profiles Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Applying anomaly detection to vehicles’ trip summaries, we develop a method allowing to derive a routine and a peculiarity anomaly profile for each vehicle. |
Francis Duval; Jean-Philippe Boucher; Mathieu Pigeon; | arxiv-cs.LG | 2022-09-26 |
| 130 | Visual Anomaly Detection Via Partition Memory Bank Module and Error Estimation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Unfortunately, the existing memory module is not fully applicable to the anomaly detection task, and the reconstruction error of the anomaly samples remains small. Towards this end, this work proposes a new unsupervised visual anomaly detection method to jointly learn effective normal features and eliminate unfavorable reconstruction errors. |
Peng Xing; Zechao Li; | arxiv-cs.CV | 2022-09-26 |
| 131 | Self-Supervised Guided Segmentation Framework for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a novel Self-Supervised Guided Segmentation Framework (SGSF) is proposed by jointly exploring effective generation method of forged anomalous samples and the normal sample features as the guidance information of segmentation for anomaly detection. |
Peng Xing; Yanpeng Sun; Zechao Li; | arxiv-cs.CV | 2022-09-26 |
| 132 | Real-time Anomaly Detection for Multivariate Data Streams Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a real-time multivariate anomaly detection algorithm for data streams based on the Probabilistic Exponentially Weighted Moving Average (PEWMA). |
Kenneth Odoh; | arxiv-cs.AI | 2022-09-25 |
| 133 | Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Unlike other reconstruction-based methods, we present a novel self-supervised masked convolutional transformer block (SSMCTB) that comprises the reconstruction-based functionality at a core architectural level. |
NEELU MADAN et. al. | arxiv-cs.CV | 2022-09-25 |
| 134 | Composite Layers for Deep Anomaly Detection on 3D Point Clouds Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Here we introduce the composite layer, a new convolutional operator for point clouds. |
Alberto Floris; Luca Frittoli; Diego Carrera; Giacomo Boracchi; | arxiv-cs.CV | 2022-09-23 |
| 135 | Special Issue on Deep Learning Modeling in Real Life: Anomaly Detection, Biomedical, Concept Analysis, Finance, Image Analysis, Recommendation Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Lazaros Iliadis; Luca Magri; | Neural computing & applications | 2022-09-23 |
| 136 | Anomaly Detection on Financial Time Series By Principal Component Analysis and Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose an approachthat aims to improve anomaly detection in financial time series, overcoming most of the inherentdifficulties. |
Stéphane Crépey; Lehdili Noureddine; Nisrine Madhar; Maud Thomas; | arxiv-q-fin.ST | 2022-09-22 |
| 137 | Oracle Analysis of Representations for Deep Open Set Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The goal of this work is to improve this methodology by providing ways of separately measuring the effectiveness of the representation learning and anomaly scoring. |
Risheek Garrepalli; | arxiv-cs.CV | 2022-09-22 |
| 138 | Improving Generalizability of Graph Anomaly Detection Models Via Data Augmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we base on the phenomenon and propose a general and novel research problem of generalized graph anomaly detection that aims to effectively identify anomalies on both the training-domain graph and unseen testing graph to eliminate potential dangers. |
Shuang Zhou; Xiao Huang; Ninghao Liu; Fu-Lai Chung; Long-Kai Huang; | arxiv-cs.LG | 2022-09-21 |
| 139 | Deep Learning Based Pipeline for Anomaly Detection and Quality Enhancement in Industrial Binder Jetting Processes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: With a use case from additive manufacturing for automotive components we present a deep-learning-based image processing pipeline. |
Alexander Zeiser; Bas van Stein; Thomas Bäck; | arxiv-cs.LG | 2022-09-21 |
| 140 | Collaborative Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering the sheer volume of items and the sparsity of user-item paired data, independently applying conventional single-task detection methods on each item quickly becomes difficult, while correlations between items are ignored. To address this multi-task anomaly detection problem, we propose collaborative anomaly detection (CAD) to jointly learn all tasks with an embedding encoding correlations among tasks. |
KE BAI et. al. | arxiv-cs.LG | 2022-09-20 |
| 141 | An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We consider the problem of building visual anomaly detection systems for mobile robots. |
Dario Mantegazza; Alessandro Giusti; Luca Maria Gambardella; Jérôme Guzzi; | arxiv-cs.CV | 2022-09-20 |
| 142 | An Unsupervised Data-Driven Anomaly Detection Approach for Adverse Health Conditions in People Living With Dementia: Cohort Study Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Sensor-based remote health monitoring can be used for the timely detection of health deterioration in people living with dementia with minimal impact on their day-to-day living. … |
Nivedita Bijlani; Ramin Nilforooshan; Samaneh Kouchaki; | JMIR aging | 2022-09-19 |
| 143 | Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Abstract: Joint detection of drivable areas and road anomalies is very important for mobile robots. Recently, many semantic segmentation approaches based on convolutional neural networks … |
Hengli Wang; Rui Fan; Yuxiang Sun; Ming Liu; | IEEE transactions on cybernetics | 2022-09-19 |
| 144 | Quantum Algorithm for Anomaly Detection of Sequences Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a quantum algorithm for ADPAAD, which can divide the subsequence elements and compute the average in parallel. |
MING-CHAO GUO et. al. | arxiv-quant-ph | 2022-09-18 |
| 145 | LogGD:Detecting Anomalies from System Logs By Graph Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a novel graph-based log anomaly detection method, LogGD, to effectively address the issue by transforming log sequences into graphs. |
Yongzheng Xie; Hongyu Zhang; Muhammad Ali Babar; | arxiv-cs.SE | 2022-09-16 |
| 146 | Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this purpose, we propose a method that utilizes the current state as well as an old state of the same generator to create good and bad quality reconstruction examples. |
Muhammad Zaigham Zaheer; Jin-Ha Lee; Arif Mahmood; Marcella Astrid; Seung-Ik Lee; | IEEE transactions on image processing : a publication of … | 2022-09-15 |
| 147 | Self-Supervised Texture Image Anomaly Detection By Fusing Normalizing Flow and Dictionary Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a strategy for anomaly detection that combines dictionary learning and normalizing flow based on the aforementioned questions. |
Yaohua Guo; Lijuan Song; Zirui Ma; | arxiv-cs.CV | 2022-09-14 |
| 148 | Anomaly Detection Under Coordinate Transformations Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: It is a well-known fact that probability densities are not invariant under coordinate transformations, so the sensitivity can depend on the initial choice of coordinates. The broader machine learning community has recently connected coordinate sensitivity with anomaly detection and our goal is to bring awareness of this issue to the growing high energy physics literature on anomaly detection. |
GREGOR KASIECZKA et. al. | arxiv-hep-ph | 2022-09-13 |
| 149 | Detecting Driver Drowsiness As An Anomaly Using LSTM Autoencoders Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an LSTM autoencoder-based architecture is utilized for drowsiness detection with ResNet-34 as feature extractor. |
Gülin Tüfekci; Alper Kayabaşi; Erdem Akagündüz; İlkay Ulusoy; | arxiv-cs.CV | 2022-09-12 |
| 150 | Hyperbolic Self-supervised Contrastive Learning Based Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: With the wide application of deep learning on graph representations, existing approaches choose to apply euclidean graph encoders as their backbone, which may lose important hierarchical information, especially in complex networks. To tackle this problem, we propose an efficient anomaly detection framework using hyperbolic self-supervised contrastive learning. |
Yuanjun Shi; | arxiv-cs.SI | 2022-09-12 |
| 151 | Multi-mode Non-Gaussian Variational Autoencoder Network with Missing Sources for Anomaly Detection of Complex Electromechanical Equipment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, the data from electromechanical equipment is usually non-Gaussian, making it difficult for the standard VAE based on Gaussian distribution to recognize the abnormal states. To solve the above problems, we proposed multi-mode non-Gaussian VAE (MNVAE) to detect anomalies from unknown distribution vibration signals without fault samples or prior knowledge. |
Qinyuan Luo; Jinglong Chen; Yanyang Zi; Yuanhong Chang; Yong Feng; | ISA transactions | 2022-09-12 |
| 152 | Self-supervised Anomaly Detection with Random-shape Pseudo-outliers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in a medical image is a challenging yet essential task. It relies on learning patterns/distributions from health data only, and no abnormal samples are available … |
Hanqiu Deng; Xingyu Li; | Annual International Conference of the IEEE Engineering in … | 2022-09-10 |
| 153 | A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the empirical study using nine publicly available datasets, we apply the most commonly-used performance evaluation metrics to typical methods under a fair implementation standard. |
YAN ZHAO et. al. | arxiv-cs.LG | 2022-09-10 |
| 154 | Deep Baseline Network for Time Series Modeling and Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop a novel deep architecture to properly extract the baseline from time series, namely Deep Baseline Network (DBLN). |
Cheng Ge; Xi Chen; Ming Wang; Jin Wang; | arxiv-cs.LG | 2022-09-09 |
| 155 | Anomaly Detection Through Unsupervised Federated Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we propose a novel method in which, through a preprocessing phase, clients are grouped into communities, each having similar majority (i.e., inlier) patterns. |
Mirko Nardi; Lorenzo Valerio; Andrea Passarella; | arxiv-cs.LG | 2022-09-09 |
| 156 | Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This criticism has grown to the point that explanation is now considered very relevant in terms of acceptability and reliability. In this paper, we addressed this issue by inspecting the ADMNC (Anomaly Detection on Mixed Numerical and Categorical Spaces) model, an existing very accurate although opaque anomaly detector capable to operate with both numerical and categorical inputs. |
Iñigo López-Riobóo Botana; Carlos Eiras-Franco; Julio Hernandez-Castro; Amparo Alonso-Betanzos; | arxiv-cs.LG | 2022-09-09 |
| 157 | Suspicious and Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this project we propose a CNN architecture to detect anomaly and suspicious activities; the activities chosen for the project are running, jumping and kicking in public places and carrying gun, bat and knife in public places. |
Shubham Deshmukh; Favin Fernandes; Monali Ahire; Devarshi Borse; Amey Chavan; | arxiv-cs.CV | 2022-09-08 |
| 158 | RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an Interpretable Anomaly Detection System (RX-ADS) for intrusion detection in CAN protocol communication in EVs. |
CHATHURIKA S. WICKRAMASINGHE et. al. | arxiv-cs.LG | 2022-09-05 |
| 159 | FIRED: A Fine-grained Robust Performance Diagnosis Framework for Cloud Applications Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide a FIne-grained Robust pErformance Diagnosis (FIRED) framework to tackle those challenges. |
Ruyue Xin; Hongyun Liu; Peng Chen; Paola Grosso; Zhiming Zhao; | arxiv-cs.DC | 2022-09-05 |
| 160 | ADTR: Anomaly Detection Transformer with Feature Reconstruction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Anomaly Detection TRansformer (ADTR) to apply a transformer to reconstruct pre-trained features. |
ZHIYUAN YOU et. al. | arxiv-cs.CV | 2022-09-05 |
| 161 | Private Anomaly Detection of Student Health Conditions Based on Wearable Sensors in Mobile Cloud Computing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Second, the health data of students are often sensitive enough, which probably impedes the integration of health data in cloud environment even renders the health data-based anomaly detection infeasible. In view of these challenges, we propose a time-efficient and privacy-aware anomaly detection solution for students with wearable sensors in mobile cloud computing environment. |
Yu Xie; Kuilin Zhang; Huaizhen Kou; Mohammad Jafar Mokarram; | Journal of cloud computing (Heidelberg, Germany) | 2022-09-05 |
| 162 | A Benchmark for Unsupervised Anomaly Detection in Multi-Agent Trajectories Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We fill the gap and propose the R-U-MAAD benchmark for unsupervised anomaly detection in multi-agent trajectories. |
Julian Wiederer; Julian Schmidt; Ulrich Kressel; Klaus Dietmayer; Vasileios Belagiannis; | arxiv-cs.RO | 2022-09-05 |
| 163 | Quickest Anomaly Detection in Sensor Networks With Unlabeled Samples Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For the two cases, practical algorithms based on the ideas of mixture likelihood ratio and/or maximum likelihood estimate are constructed. |
Zhongchang Sun; Shaofeng Zou; | arxiv-eess.SP | 2022-09-03 |
| 164 | Appliance-Level Anomaly Detection By Using Control Charts and Artificial Neural Networks with Power Profiles Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, in order to contribute to the works that use appliance power profiles for anomaly detection, a novel Appliance Monitoring and Anomaly Detection System (AM-ADS) is presented. |
Hanife Apaydin-Özkan; | Sensors (Basel, Switzerland) | 2022-09-02 |
| 165 | NnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: It is also difficult to assess whether a task generalises well for universal anomaly detection, as they are often only tested on a limited range of anomalies. To assist with this we have developed nnOOD, a framework that adapts nnU-Net to allow for comparison of self-supervised anomaly localisation methods. |
Matthew Baugh; Jeremy Tan; Athanasios Vlontzos; Johanna P. Müller; Bernhard Kainz; | arxiv-cs.CV | 2022-09-02 |
| 166 | Neuromorphic Implementation of ECG Anomaly Detection Using Delay Chains Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we propose to extend the memory capacity of a spiking neural network by using parallel delay chains. |
Stefan Gerber; Marc Steiner; Maryada; Giacomo Indiveri; Elisa Donati; | arxiv-eess.SP | 2022-09-02 |
| 167 | Magnetic Anomaly Detection Via A Combination Approach of Minimum Entropy and Gradient Orthogonal Functions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Aiming at the problem of magnetic anomaly detection under low signal-to-noise ratio, a full magnetic gradient detection via minimum entropy and gradient orthonormal basis function … |
JIAQI ZHOU et. al. | ISA transactions | 2022-09-01 |
| 168 | Deep Anomaly Detection and Search Via Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Semi-supervised Anomaly Detection (AD) is a kind of data mining task which aims at learning features from partially-labeled datasets to help detect outliers. In this paper, we classify existing semi-supervised AD methods into two categories: unsupervised-based and supervised-based, and point out that most of them suffer from insufficient exploitation of labeled data and under-exploration of unlabeled data. |
Chao Chen; Dawei Wang; Feng Mao; Zongzhang Zhang; Yang Yu; | arxiv-cs.LG | 2022-08-31 |
| 169 | Denoising Architecture for Unsupervised Anomaly Detection in Time-Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The LSTM Autoencoder is an Encoder-Decoder scheme for Anomaly Detection based on Long Short Term Memory Networks that learns to reconstruct time-series behavior and then uses reconstruction error to identify abnormalities. We introduce the Denoising Architecture as a complement to this LSTM Encoder-Decoder model and investigate its effect on real-world as well as artificially generated datasets. |
Wadie Skaf; Tomáš Horváth; | arxiv-cs.LG | 2022-08-30 |
| 170 | Anomaly Detection Using Contrastive Normalizing Flows Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to use an unlabelled auxiliary dataset and a probabilistic outlier score for anomaly detection. |
Robert Schmier; Ullrich Köthe; Christoph-Nikolas Straehle; | arxiv-cs.LG | 2022-08-30 |
| 171 | Deep Autoencoders for Anomaly Detection in Textured Images Using CW-SSIM Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: A relevant example is the analysis of tissues and other products that in normal conditions conform to a specific texture, while defects introduce changes in the normal pattern. We address the anomaly detection problem by training a deep autoencoder, and we show that adopting a loss function based on Complex Wavelet Structural Similarity (CW-SSIM) yields superior detection performance on this type of images compared to traditional autoencoder loss functions. |
Andrea Bionda; Luca Frittoli; Giacomo Boracchi; | arxiv-cs.CV | 2022-08-30 |
| 172 | RUAD: Unsupervised Anomaly Detection in HPC Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Unsupervised anomaly detection approaches based on clustering, aimed at alleviating the need for accurate anomaly data, have so far shown poor performance. In this work, we overcome these limitations by proposing RUAD, a novel Recurrent Unsupervised Anomaly Detection model. |
Martin Molan; Andrea Borghesi; Daniele Cesarini; Luca Benini; Andrea Bartolini; | arxiv-cs.LG | 2022-08-28 |
| 173 | Plant Health Index As An Anomaly Detection Tool for Oil Refinery Processes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Early detection of significant abnormal changes is highly desirable for oil refinery processes, which consist of sophisticated unit operations handling hazardous and flammable … |
Fawaz S Al-Anzi; Haitham M S Lababidi; Ghanima Al-Sharrah; Suad A Al-Radwan; Ho Joon Seo; | Scientific reports | 2022-08-25 |
| 174 | Anomaly Detection in Satellite Telemetry Data Using A Sparse Feature-Based Method Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection based on telemetry data is a major issue in satellite health monitoring which can identify unusual or unexpected events, helping to avoid serious accidents and … |
Jiahui He; Zhijun Cheng; Bo Guo; | Sensors (Basel, Switzerland) | 2022-08-24 |
| 175 | Squat Detection of Railway Switches and Crossings Using Wavelets and Isolation Forest Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Railway switches and crossings (S&Cs) are critical, high-value assets in railway networks. A single failure of such an asset could result in severe network disturbance and … |
Yang Zuo; Florian Thiery; Praneeth Chandran; Johan Odelius; Matti Rantatalo; | Sensors (Basel, Switzerland) | 2022-08-24 |
| 176 | ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a method to leverage weak/noisy labels (e.g., risk scores generated by machine rules for detecting malware) that are cheaper to obtain for anomaly detection. |
Yue Zhao; Guoqing Zheng; Subhabrata Mukherjee; Robert McCann; Ahmed Awadallah; | arxiv-cs.LG | 2022-08-23 |
| 177 | An Anomaly Detection Approach for Backdoored Neural Networks: Face Recognition As A Case Study Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel backdoored network detection method based on the principle of anomaly detection, involving access to the clean part of the training data and the trained network. |
Alexander Unnervik; Sébastien Marcel; | arxiv-cs.CV | 2022-08-22 |
| 178 | Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we proposed a two-stage model that combines the Birch clustering algorithm and MLP classifier to improve the performance of network anomaly multi-classification. |
Yuhua Yin; Julian Jang-Jaccard; Fariza Sabrina; Jin Kwak; | arxiv-cs.CR | 2022-08-20 |
| 179 | Feature Selection for Fault Detection and Prediction Based on Event Log Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, when anomaly detection is performed at the subsystem level, analyzing all features becomes expensive and unnecessary. To mitigate this problem, we develop a feature selection method for log-based anomaly detection and prediction, largely improving the effectiveness and efficiency. |
Zhong Li; Matthijs van Leeuwen; | arxiv-cs.LG | 2022-08-19 |
| 180 | ResNet-AE for Radar Signal Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Radar signal anomaly detection is an effective method to detect potential threat targets. Given the low of the traditional AE model and the complex network of GAN, an anomaly … |
Donghang Cheng; Youchen Fan; Shengliang Fang; Mengtao Wang; Han Liu; | Sensors (Basel, Switzerland) | 2022-08-19 |
| 181 | Automatic Hemorrhage Detection From Color Doppler Ultrasound Using A Generative Adversarial Network (GAN)-Based Anomaly Detection Method Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Hemorrhage control has been identified as a priority focus area both for civilian and military populations in the United States because exsanguination is the most common cause of … |
JHIMLI MITRA et. al. | IEEE journal of translational engineering in health and … | 2022-08-19 |
| 182 | An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper proposes an anomaly detection method based on unsupervised Short- and Long-term Mask Representation learning (SLMR). |
Qiucheng Miao; Chuanfu Xu; Jun Zhan; Dong zhu; Chengkun Wu; | arxiv-cs.LG | 2022-08-19 |
| 183 | Challenges in Applying Robotics to Retail Store Management Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: An autonomous retail store management system entails inventory tracking, store monitoring, and anomaly correction. Recent attempts at autonomous retail store management have faced … |
VARTIKA SENGAR et. al. | arxiv-cs.RO | 2022-08-18 |
| 184 | AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: However, existing graph anomaly detection approaches do not leverage heterogeneity in attributed networks, which is highly related to anomaly detection. In light of this problem, we propose AHEAD: a heterogeneity-aware unsupervised graph anomaly detection approach based on the encoder-decoder framework. |
SHUJIE YANG et. al. | arxiv-cs.SI | 2022-08-17 |
| 185 | Detecting Anomalous Content in Dairy with Whole Metagenome Sequencing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To that end, the objective of the research presented here was to assess the feasibility of using whole metagenome shotgun sequencing data as input into anomaly detection algorithms using fluid milk as a model system. |
N. HAIMINEN et. al. | bio.microbiology | 2022-08-17 |
| 186 | Bayesian Estimation of Oscillator Parameters: Toward Anomaly Detection and Cyber-Physical System Security Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present Bayesian inference of unknown parameters associated with a generic actuator considered as a representative vital element of a cyber-physical system. |
Joseph M Lukens; Ali Passian; Srikanth Yoginath; Kody J H Law; Joel A Dawson; | Sensors (Basel, Switzerland) | 2022-08-16 |
| 187 | Federated Multi-Discriminator BiWGAN-GP Based Collaborative Anomaly Detection for Virtualized Network Slicing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering the powerful ability of generative adversarial network (GAN) in capturing the distribution from complex data, we design a new multi-discriminator Bidirectional Wasserstein GAN with Gradient Penalty (BiWGAN-GP) model to learn the normal data distribution from high-dimensional resource metrics datasets that are spread on multiple VM monitors. |
Weili Wang; Chengchao Liang; Lun Tang; Halim Yanikomeroglu; Qianbin Chen; | arxiv-cs.NI | 2022-08-16 |
| 188 | Taxonomy of Anomaly Detection Techniques in Crowd Scenes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the widespread use of closed-circuit television (CCTV) surveillance systems in public areas, crowd anomaly detection has become an increasingly critical aspect of the … |
Amnah Aldayri; Waleed Albattah; | Sensors (Basel, Switzerland) | 2022-08-14 |
| 189 | Adaptive Model Pooling for Online Deep Anomaly Detection from A Complex Evolving Data Stream Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper presents a framework for online deep anomaly detection, ARCUS, which can be instantiated with any autoencoder-based deep anomaly detection methods. |
Susik Yoon; Youngjun Lee; Jae-Gil Lee; Byung Suk Lee; | kdd | 2022-08-12 |
| 190 | Long-Short Term Memory Network-Based Monitoring Data Anomaly Detection of A Long-Span Suspension Bridge Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Structural health monitoring (SHM) systems have been widely applied in long-span bridges and a large amount of SHM data is continually collected. The harsh environment of sensors … |
Jianliang Zhang; Jian Zhang; Zhishen Wu; | Sensors (Basel, Switzerland) | 2022-08-12 |
| 191 | Augmenting Log-based Anomaly Detection Models to Reduce False Anomalies with Human Feedback Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Through the study, we identify four typical anti-patterns that affect the detection results the most. Based on these patterns, we propose HiLog, an effective human-in-the-loop log-based anomaly detection approach that integrates human knowledge to augment anomaly detection models. |
Tong Jia; Ying Li; Yong Yang; Gang Huang; Zhonghai Wu; | kdd | 2022-08-12 |
| 192 | Framing Algorithmic Recourse for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an approach-Context preserving Algorithmic Recourse for Anomalies in Tabular data(CARAT), that is effective, scalable, and agnostic to the underlying anomaly detection model. |
Debanjan Datta; Feng Chen; Naren Ramakrishnan; | kdd | 2022-08-12 |
| 193 | PAC-Wrap: Semi-Supervised PAC Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Given their safety-criticality, these applications benefit from provable bounds on various errors in anomaly detection. To achieve this goal in the semi-supervised setting, we propose to provide Probably Approximately Correct (PAC) guarantees on the false negative and false positive detection rates for anomaly detection algorithms. |
Shuo Li; Xiayan Ji; Edgar Dobriban; Oleg Sokolsky; Insup Lee; | kdd | 2022-08-12 |
| 194 | Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: First, they are limited to the batch case, whereas the online case is more actionable. Second, these algorithms exhibit poor scalability beyond tens of thousands of datapoints. In this work we introduce DAMP, a novel algorithm that addresses both these issues. |
Yue Lu; Renjie Wu; Abdullah Mueen; Maria A. Zuluaga; Eamonn Keogh; | kdd | 2022-08-12 |
| 195 | Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce Fused Sparse Autoencoder and Graph Net (FuSAGNet), which jointly optimizes reconstruction and forecasting while explicitly modeling the relationships within multivariate time series. |
Siho Han; Simon S. Woo; | kdd | 2022-08-12 |
| 196 | Local Evaluation of Time Series Anomaly Detection Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To cope with the above problems, we propose a theoretically grounded, robust, parameter-free and interpretable extension to precision/recall metrics, based on the concept of "affiliation” between the ground truth and the prediction sets. |
Alexis Huet; Jose Manuel Navarro; Dario Rossi; | kdd | 2022-08-12 |
| 197 | Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose a multi-pattern adversarial learning one-class classification framework, which allows us to use both the generator and the discriminator of an adversarial model for efficient ASD. |
YU SHA et. al. | kdd | 2022-08-12 |
| 198 | Anomaly Segmentation Model for Defects Detection in Electroluminescence Images of Heterojunction Solar Cells Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a deep-learning-based automatic detection model SeMaCNN for classification and semantic segmentation of electroluminescent images for solar cell quality evaluation and anomalies detection. |
ALEXEY KOROVIN et. al. | arxiv-cs.CV | 2022-08-11 |
| 199 | Consistency-based Self-supervised Learning for Temporal Anomaly Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we get inspired by recent advances within the field of self-supervised learning and ask the model to yield the same scores for different augmentations of the same video sequence. |
Aniello Panariello; Angelo Porrello; Simone Calderara; Rita Cucchiara; | arxiv-cs.CV | 2022-08-10 |
| 200 | A Pattern Dictionary Method for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning … |
Elyas Sabeti; Sehong Oh; Peter X K Song; Alfred O Hero; | Entropy (Basel, Switzerland) | 2022-08-09 |
| 201 | Real-Time Anomaly Detection for An ADMM-Based Optimal Transmission Frequency Management System for IoT Devices Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In this paper, we investigate different scenarios of anomaly detection on decentralised Internet of Things (IoT) applications. Specifically, an anomaly detector is devised to … |
Hongde Wu; Noel E O’Connor; Jennifer Bruton; Amy Hall; Mingming Liu; | Sensors (Basel, Switzerland) | 2022-08-09 |
| 202 | Measuring Internal Inequality in Capsule Networks for Supervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In this paper we explore the use of income inequality metrics such as Gini or Palma coefficients as a tool to identify anomalies via capsule networks. We demonstrate how the … |
Bogdan Kirillov; Maxim Panov; | Scientific reports | 2022-08-09 |
| 203 | Time Series Anomaly Detection Model Based on Multi-Features Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: For Internet information services, it is very important to closely monitor a large number of key time series data generated by core business for anomaly detection. Although there … |
Hengyao Tang; Qingdong Wang; Guosong Jiang; | Computational intelligence and neuroscience | 2022-08-08 |
| 204 | Constructing Large-Scale Real-World Benchmark Datasets for AIOps Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The lack of public large-scale real-world datasets has prevented researchers and engineers from enhancing the development of AIOps. To tackle this dilemma, in this work, we introduce three public real-world, large-scale datasets about AIOps, mainly aiming at KPI anomaly detection, root cause localization on multi-dimensional data, and failure discovery and diagnosis. |
ZEYAN LI et. al. | arxiv-cs.SE | 2022-08-08 |
| 205 | Author Correction: Dental Anomaly Detection Using Intraoral Photos Via Deep Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
RONILO RAGODOS et. al. | Scientific reports | 2022-08-08 |
| 206 | HaloAE: An HaloNet Based Local Transformer Auto-Encoder for Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we introduce HaloAE, the first auto-encoder based on a local 2D version of Transformer with HaloNet. |
E. MATHIAN et. al. | arxiv-cs.CV | 2022-08-06 |
| 207 | Detecting Multivariate Time Series Anomalies with Zero Known Label Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose MTGFlow, an unsupervised anomaly detection approach for multivariate time series anomaly detection via dynamic graph and entity-aware normalizing flow, leaning only on a widely accepted hypothesis that abnormal instances exhibit sparse densities than the normal. |
Qihang Zhou; Jiming Chen; Haoyu Liu; Shibo He; Wenchao Meng; | arxiv-cs.LG | 2022-08-03 |
| 208 | Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Time series anomaly detection (TSAD) is an important data mining task with numerous applications in the IoT era. In recent years, a large number of deep neural network-based … |
Wenkai Li; Cheng Feng; Ting Chen; Jun Zhu; | arxiv-cs.LG | 2022-08-03 |
| 209 | DSR — A Dual Subspace Re-projection Network for Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose an architecture based on quantized feature space representation with dual decoders, DSR, that avoids the image-level anomaly synthesis requirement. |
Vitjan Zavrtanik; Matej Kristan; Danijel Skočaj; | arxiv-cs.CV | 2022-08-02 |
| 210 | Unsupervised Quantum Machine Learning for Fraud Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We discuss the prospects of fraud detection with near- and mid-term quantum hardware, and describe possible future improvements. |
Oleksandr Kyriienko; Einar B. Magnusson; | arxiv-quant-ph | 2022-08-01 |
| 211 | Curved Geometric Networks for Visual Anomaly Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate benefits of the curved space for analyzing anomalies or out-of-distribution objects in data. |
JIE HONG et. al. | arxiv-cs.CV | 2022-08-01 |
| 212 | Could Ultrasound Midwifery Training Increase Antenatal Detection of Congenital Anomalies in Ghana? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: As part of World Health Organization (WHO) 2016 updated antenatal care (ANC) guidelines routine ultrasonography is recommended, including to detect congenital anomalies. The Ghana … |
Alhassan Abdul-Mumin; Lauren N Rotkis; Solomon Gumanga; Emily E Fay; Donna M Denno; | PloS one | 2022-08-01 |
| 213 | The Robust Multi-Scale Deep-SVDD Model for Anomaly Online Detection of Rolling Bearings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Aiming at the online detection problem of rolling bearings, the limited amount of target bearing data leads to insufficient model in training and feature representation. It is … |
Linlin Kou; Jiaxian Chen; Yong Qin; Wentao Mao; | Sensors (Basel, Switzerland) | 2022-07-29 |
| 214 | Concept Drift Challenge in Multimedia Anomaly Detection: A Case Study with Facial Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we systematically investigate the effect of concept drift on various detection models and propose a modified Adaptive Gaussian Mixture Model (AGMM) based framework for anomaly detection in multimedia data. |
Pratibha Kumari; Priyankar Choudhary; Pradeep K. Atrey; Mukesh Saini; | arxiv-cs.CV | 2022-07-27 |
| 215 | Improving Network-Based Anomaly Detection in Smart Home Environment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The Smart Home (SH) has become an appealing target of cyberattacks. Due to the limitation of hardware resources and the various operating systems (OS) of current SH devices, … |
Xiaonan Li; Hossein Ghodosi; Chao Chen; Mangalam Sankupellay; Ickjai Lee; | Sensors (Basel, Switzerland) | 2022-07-27 |
| 216 | Learning Appearance-motion Normality for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose spatial-temporal memories augmented two-stream auto-encoder framework, which learns the appearance normality and motion normality independently and explores the correlations via adversarial learning. |
YANG LIU et. al. | arxiv-cs.CV | 2022-07-27 |
| 217 | Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Consequently, they often learn a biased, inaccurate normality boundary. This paper proposes a novel one-class learning approach, named calibrated one-class classification, to tackle this problem. |
HONGZUO XU et. al. | arxiv-cs.LG | 2022-07-25 |
| 218 | Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, the approaches proposed so far in the literature have severe limitations: they either require prior domain knowledge used to design the anomaly discovery algorithms, or become cumbersome and expensive to use in situations with recurrent anomalies of the same type. In this work, we address these problems, and propose an unsupervised method suitable for domain agnostic subsequence anomaly detection. |
Paul Boniol; Themis Palpanas; | arxiv-cs.LG | 2022-07-25 |
| 219 | A General-purpose Method for Applying Explainable AI for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We argue that explainability is principally an algorithmic task and interpretability is principally a cognitive task, and draw on insights from the cognitive sciences to propose a general-purpose method for practical diagnosis using explained anomalies. |
John Sipple; Abdou Youssef; | arxiv-cs.LG | 2022-07-23 |
| 220 | IRC-Safe Graph Autoencoder for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection through employing machine learning techniques has emerged as a novel powerful tool in the search for new physics beyond the Standard Model. Historically similar … |
OLIVER ATKINSON et. al. | Frontiers in artificial intelligence | 2022-07-22 |
| 221 | Development of Monitoring Systems for Anomaly Detection Using ASTD Specifications Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper provides a model for detecting point anomalies using the unsupervised non-parametric technique Kernel Density Estimation to estimate the probability density of event occurrence. |
El Jabri Chaymae; Frappier Marc; Ecarot Thibaud; Tardif Pierre-Martin; | arxiv-cs.FL | 2022-07-22 |
| 222 | Anomaly Detection in Fundus Images By Self-adaptive Decomposition Via Local and Color Based Sparse Coding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in color fundus images is challenging due to the diversity of anomalies. The current studies detect anomalies from fundus images by learning their background … |
YUCHEN DU et. al. | Biomedical optics express | 2022-07-21 |
| 223 | Comparative Study on Supervised Versus Semi-supervised Machine Learning for Anomaly Detection of In-vehicle CAN Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, the CAN bus is designed to be vulnerable to various attacks due to its lack of security mechanisms. To enhance the security of in-vehicle networks and promote the research in this area, based upon a large scale of CAN network traffic data with the extracted valuable features, this study comprehensively compared fully-supervised machine learning with semi-supervised machine learning methods for CAN message anomaly detection. |
Yongqi Dong; Kejia Chen; Yinxuan Peng; Zhiyuan Ma; | arxiv-cs.LG | 2022-07-20 |
| 224 | Unsupervised Industrial Anomaly Detection Via Pattern Generative and Contrastive Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Moreover, they have a memory library by clustering the feature of normal images essentially, which cause it is not robust to texture change. To this end, we propose the Vision Transformer based (VIT-based) unsupervised anomaly detection network. |
Jianfeng Huang; Chenyang Li; Yimin Lin; Shiguo Lian; | arxiv-cs.CV | 2022-07-20 |
| 225 | IoT Anomaly Detection Methods and Applications: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The survey considers 64 papers among recent publications published between January 2019 and July 2021. |
Ayan Chatterjee; Bestoun S. Ahmed; | arxiv-cs.SE | 2022-07-19 |
| 226 | Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To solve this problem, we propose Partial and Asymmetric Supervised Contrastive Learning (PASCL), which explicitly encourages the model to distinguish between tail-class in-distribution samples and OOD samples. |
HAOTAO WANG et. al. | icml | 2022-07-15 |
| 227 | Latent Outlier Exposure for Anomaly Detection with Contaminated Data Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose a strategy for training an anomaly detector in the presence of unlabeled anomalies that is compatible with a broad class of models. |
Chen Qiu; Aodong Li; Marius Kloft; Maja Rudolph; Stephan Mandt; | icml | 2022-07-15 |
| 228 | Rethinking Graph Neural Networks for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Our crucial observation is the existence of anomalies will lead to the ‘right-shift’ phenomenon, that is, the spectral energy distribution concentrates less on low frequencies and more on high frequencies. |
Jianheng Tang; Jiajin Li; Ziqi Gao; Jia Li; | icml | 2022-07-15 |
| 229 | Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we model sensor dependency and stochasticity within MTS by developing an embedding-guided probabilistic generative network. |
WENCHAO CHEN et. al. | icml | 2022-07-15 |
| 230 | Anomal-E: A Self-Supervised Network Intrusion Detection System Based on Graph Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The majority of current implementations of GNN-based Network Intrusion Detection Systems (NIDSs) rely heavily on labelled network traffic which can not only restrict the amount and structure of input traffic, but also the NIDSs potential to adapt to unseen attacks. To overcome these restrictions, we present Anomal-E, a GNN approach to intrusion and anomaly detection that leverages edge features and graph topological structure in a self-supervised process. |
Evan Caville; Wai Weng Lo; Siamak Layeghy; Marius Portmann; | arxiv-cs.LG | 2022-07-14 |
| 231 | Memory-augmented Skip-connected Autoencoder for Unsupervised Anomaly Detection of Rocket Engines with Multi-source Fusion Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, due to the indistinct features of signals under the interference of extreme conditions and the weak distinguishing ability to exist unsupervised methods, it is difficult to distinguish abnormal samples from normal samples, which leads to the failure of reliable anomaly detection. Aiming at this problem, this paper proposed an unsupervised learning algorithm named Memory-augmented skip-connected deep autoencoder (Mem-SkipAE) for anomaly detection of rocket engines with multi-source data fusion. |
Haodong Yan; Zijun Liu; Jinglong Chen; Yong Feng; Jun Wang; | ISA transactions | 2022-07-14 |
| 232 | Experiments on Anomaly Detection in Autonomous Driving By Forward-Backward Style Transfers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Especially inspired by works on anomaly detection based on image resynthesis, we propose a novel approach for anomaly detection through style transfer. |
Daniel Bogdoll; Meng Zhang; Maximilian Nitsche; J. Marius Zöllner; | arxiv-cs.CV | 2022-07-13 |
| 233 | Spatial Anomaly Detection with Optimal Transport Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This manuscript outlines an automated anomaly detection framework for jet engines. |
Pranay Seshadri; Andrew B. Duncan; George Thorne; Raul Vazquez Diaz; | arxiv-stat.AP | 2022-07-13 |
| 234 | Anomaly Score-Based Risk Early Warning System for Rapidly Controlling Food Safety Risk Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Food safety is a high-priority issue for all countries. Early warning analysis and risk control are essential for food safety management practices. This paper innovatively … |
ENGUANG ZUO et. al. | Foods (Basel, Switzerland) | 2022-07-13 |
| 235 | GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we pose an entity-wise multivariate time-series anomaly detection problem that considers the time-series of each unique entity. |
Xu Chen; Qiu Qiu; Changshan Li; Kunqing Xie; | sigir | 2022-07-12 |
| 236 | On The Robustness and Anomaly Detection of Sparse Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that sparsity can make networks more robust and better anomaly detectors. |
MORGANE AYLE et. al. | arxiv-cs.LG | 2022-07-09 |
| 237 | Dental Anomaly Detection Using Intraoral Photos Via Deep Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Children with orofacial clefting (OFC) present with a wide range of dental anomalies. Identifying these anomalies is vital to understand their etiology and to discern the complex … |
RONILO RAGODOS et. al. | Scientific reports | 2022-07-08 |
| 238 | Active Learning-based Isolation Forest (ALIF): Enhancing Anomaly Detection in Decision Support Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The use of unsupervised models to overcome the lack of labels often fails to catch domain specific anomalies as they rely on general definitions of outlier. This paper suggests a new active learning based approach, ALIF, to solve this problem by reducing the number of required labels and tuning the detector towards the definition of anomaly provided by the user. |
Elisa Marcelli; Tommaso Barbariol; Gian Antonio Susto; | arxiv-cs.LG | 2022-07-08 |
| 239 | Dual Attention-Based Industrial Surface Defect Detection with Consistency Loss Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In industrial production, flaws and defects inevitably appear on surfaces, resulting in unqualified products. Therefore, surface defect detection plays a key role in ensuring … |
Xuyang Li; Yu Zheng; Bei Chen; Enrang Zheng; | Sensors (Basel, Switzerland) | 2022-07-08 |
| 240 | GCN-based Multi-task Representation Learning for Anomaly Detection in Attributed Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new architecture on anomaly detection. |
Venus Haghighi; Behnaz Soltani; Adnan Mahmood; Quan Z. Sheng; Jian Yang; | arxiv-cs.LG | 2022-07-08 |
| 241 | Deep Learning for Anomaly Detection in Log Data: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: The survey does not quantitatively compare existing approaches but instead aims to help readers understand relevant aspects of different model architectures and emphasizes open issues for future work. |
Max Landauer; Sebastian Onder; Florian Skopik; Markus Wurzenberger; | arxiv-cs.LG | 2022-07-08 |
| 242 | Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper develops a unified embedding model for signed networks to disentangle the intertwined balance structure and anomaly effect, which can greatly facilitate the downstream analysis, including community detection, anomaly detection, and network inference. |
Haoran Zhang; Junhui Wang; | arxiv-cs.SI | 2022-07-07 |
| 243 | Leveraging Log Instructions in Log-based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose a method for reliable and practical anomaly detection from system logs. |
Jasmin Bogatinovski; Gjorgji Madjarov; Sasho Nedelkoski; Jorge Cardoso; Odej Kao; | arxiv-cs.AI | 2022-07-07 |
| 244 | Red PANDA: Disambiguating Anomaly Detection By Removing Nuisance Factors Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Breaking from previous research, we present a new anomaly detection method that allows operators to exclude an attribute from being considered as relevant for anomaly detection. |
Niv Cohen; Jonathan Kahana; Yedid Hoshen; | arxiv-cs.CV | 2022-07-07 |
| 245 | DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Consequently, hybrid algorithms present an attractive research goal. |
Matej Grcić; Petra Bevandić; Siniša Šegvić; | arxiv-cs.CV | 2022-07-06 |
| 246 | Leveraging Trajectory Prediction for Pedestrian Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose to leverage trajectory localization and prediction for unsupervised pedestrian anomaly event detection. |
Asiegbu Miracle Kanu-Asiegbu; Ram Vasudevan; Xiaoxiao Du; | arxiv-cs.CV | 2022-07-05 |
| 247 | BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present BiPOCO, a Bi-directional trajectory predictor with POse COnstraints, for detecting anomalous activities of pedestrians in videos. |
Asiegbu Miracle Kanu-Asiegbu; Ram Vasudevan; Xiaoxiao Du; | arxiv-cs.CV | 2022-07-05 |
| 248 | Deep Contrastive One-Class Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To overcome the shortcomings, a deep Contrastive One-Class Anomaly detection method of time series (COCA) is proposed by authors, following the normality assumptions of CL and one-class classification. |
RUI WANG et. al. | arxiv-cs.LG | 2022-07-04 |
| 249 | Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Different from existing anomaly detection strategies which do not consider any property of unavailable abnormal data during model development, a task-oriented self-supervised learning approach is proposed here which makes use of available normal EEGs and expert knowledge about abnormal EEGs to train a more effective feature extractor for the subsequent development of anomaly detector. |
YAOJIA ZHENG et. al. | arxiv-cs.LG | 2022-07-04 |
| 250 | Augment to Detect Anomalies with Continuous Labelling Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to solve anomaly detection as a supervised regression problem. |
Vahid Reza Khazaie; Anthony Wong; Yalda Mohsenzadeh; | arxiv-cs.CV | 2022-07-03 |
| 251 | Anomaly Detection with Adversarially Learned Perturbations of Latent Space Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we have designed an adversarial framework consisting of two competing components, an Adversarial Distorter, and an Autoencoder. |
Vahid Reza Khazaie; Anthony Wong; John Taylor Jewell; Yalda Mohsenzadeh; | arxiv-cs.CV | 2022-07-03 |
| 252 | Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Through analysis, we posit that this is because the models struggle to distinguish the minority tail-class in-distribution samples, from the true OOD samples, making the tail classes more prone to be falsely detected as OOD. To solve this problem, we propose Partial and Asymmetric Supervised Contrastive Learning (PASCL), which explicitly encourages the model to distinguish between tail-class in-distribution samples and OOD samples. |
HAOTAO WANG et. al. | arxiv-cs.CV | 2022-07-03 |
| 253 | Anomaly Explanation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate the importance of anomaly explanation, the areas still needing investigation based upon our previous contributions to the field, and the future directions that will be explored. |
Véronne Yepmo; | ijcai | 2022-07-01 |
| 254 | Anomaly Detection By Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number of anomalies are assumed to be available at the training stage, but they are assumed to be collected only from several anomaly types, leaving the majority of anomaly types not represented in the collected anomaly dataset at all. |
Bowen Tian; Qinliang Su; Jian Yin; | ijcai | 2022-07-01 |
| 255 | Multivariate Time Series Anomaly Detection with Few Positive Samples Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This practical situation calls for methodologies to leverage these small number of anomaly events to create a better anomaly detector. In this paper, we introduce two methodologies to address the needs of this practical situation and compared them with recently developed state of the art techniques. |
Feng Xue; Weizhong Yan; | arxiv-cs.LG | 2022-07-01 |
| 256 | Constrained Adaptive Projection with Pretrained Features for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose an anomaly detection framework called constrained adaptive projection with pretrained features (CAP). |
Xingtai Gui; Di Wu; Yang Chang; Shicai Fan; | ijcai | 2022-07-01 |
| 257 | Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the performance of the anomaly detectors under data contamination and construct a data-efficient countermeasure against data contamination. |
Shuang Wu; Jingyu Zhao; Guangjian Tian; | ijcai | 2022-07-01 |
| 258 | CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we empirically show the significance of this hardness bias present in a range of recent deep anomaly detection methods. To mitigate this, we propose an efficient and plug-and-play error calibration method which mitigates this hardness bias in the anomaly scoring without the need to retrain the model. |
Ailin Deng; Adam Goodge; Lang Yi Ang; Bryan Hooi; | ijcai | 2022-07-01 |
| 259 | Neural Contextual Anomaly Detection for Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We introduce Neural Contextual Anomaly Detection (NCAD), a framework for anomaly detection on time series that scales seamlessly from the unsupervised to supervised setting, and is applicable to both univariate and multivariate time series. |
Chris U. Carmona; François-Xavier Aubet; Valentin Flunkert; Jan Gasthaus; | ijcai | 2022-07-01 |
| 260 | HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose HashNWalk, an incremental algorithm that detects anomalies in a stream of hyperedges. |
Geon Lee; Minyoung Choe; Kijung Shin; | ijcai | 2022-07-01 |
| 261 | GRELEN: Multivariate Time Series Anomaly Detection from The Perspective of Graph Relational Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel Graph Relational Learning Network (GReLeN) to detect multivariate time series anomalies from the perspective of between-sensor dependence relationship learning. |
Weiqi Zhang; Chen Zhang; Fugee Tsung; | ijcai | 2022-07-01 |
| 262 | Ontology-Based Anomaly Detection for Air Traffic Control Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents ATC-Sense, an ADS-B anomaly detection system based on ontologies. |
Christopher Neal; Jean-Yves De Miceli; David Barrera; José Fernandez; | arxiv-cs.CR | 2022-07-01 |
| 263 | Graph Regularized Autoencoder and Its Application in Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the success of geodesic distance approximators such as ISOMAP, we propose to use a minimum spanning tree (MST), a graph-based algorithm, to approximate the local neighborhood structure and generate structure-preserving distances among data points. |
Imtiaz Ahmed; Travis Galoppo; Xia Hu; Yu Ding; | IEEE transactions on pattern analysis and machine … | 2022-07-01 |
| 264 | Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract) Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, and especially as the literature continues to expand, an extensive evaluation of every anomaly detection method is simply not feasible. To reduce this evaluation burden, we present guidelines to intelligently choose the optimal anomaly detection methods based on the characteristics the time series displays such as seasonality, trend, level change concept drift, and missing time steps. |
Cynthia Freeman; Jonathan Merriman; Ian Beaver; Abdullah Mueen; | ijcai | 2022-07-01 |
| 265 | Raising The Bar in Graph-level Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: By drawing on ideas from self-supervised learning and transformation learning, we present a new deep learning approach that significantly improves existing deep one-class approaches by fixing some of their known problems, including hypersphere collapse and performance flip. |
Chen Qiu; Marius Kloft; Stephan Mandt; Maja Rudolph; | ijcai | 2022-07-01 |
| 266 | Learning Citywide Patterns of Life from Trajectory Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To learn patterns of life, we adapt Grow When Required (GWR) episodic memory from research in computational biology and neurorobotics to a new domain of geospatial analysis. |
Mark Tenzer; Zeeshan Rasheed; Khurram Shafique; | arxiv-cs.LG | 2022-06-30 |
| 267 | DGraph: A Large-Scale Financial Dataset for Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, this paper present DGraph, a real-world dynamic graph in the finance domain. |
XUANWEN HUANG et. al. | arxiv-cs.SI | 2022-06-30 |
| 268 | A Causal Approach to Detecting Multivariate Time-series Anomalies and Root Causes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we formulate the anomaly detection problem from a causal perspective and view anomalies as instances that do not follow the regular causal mechanism to generate the multivariate data. |
Wenzhuo Yang; Kun Zhang; Steven C. H. Hoi; | arxiv-cs.LG | 2022-06-30 |
| 269 | Interpretable Anomaly Detection in Echocardiograms with Dynamic Variational Trajectory Models Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose a novel anomaly detection method for echocardiogram videos. |
ALAIN RYSER et. al. | arxiv-cs.LG | 2022-06-30 |
| 270 | Online Anomaly Detection Based On Reservoir Sampling and LOF for IoT Devices Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In the paper, we analyse the processing pipeline for anomaly detection and implementation of the Local Outliner Factor (LOF) algorithm on a MCU. |
Tomasz Szydlo; | arxiv-cs.LG | 2022-06-28 |
| 271 | Unsupervised Anomaly Detection By Robust Density Estimation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Density estimation is a widely used method for unsupervised anomaly detection. However, the presence of anomalies in training data may severely impact the density estimation … |
Boyang Liu; Pang-Ning Tan; Jiayu Zhou; | Proceedings of the … AAAI Conference on Artificial … | 2022-06-28 |
| 272 | Intrinsic Anomaly Detection for Multi-Variate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel, practically relevant variation of the anomaly detection problem in multi-variate time series: intrinsic anomaly detection. |
STEPHAN RABANSER et. al. | arxiv-cs.LG | 2022-06-28 |
| 273 | DPOAD: Differentially Private Outsourcing of Anomaly Detection Through Iterative Sensitivity Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Such a conflict is recently resolved under a local analysis setting with trusted analysts (where no outsourcing is involved) through moving the focus of differential privacy (DP) guarantee from all to only benign entries. In this paper, we observe that such an approach is not directly applicable to the outsourcing setting, because data owners do not know which entries are benign prior to outsourcing, and hence cannot selectively apply DP on data entries. |
MEISAM MOHAMMADY et. al. | arxiv-cs.CR | 2022-06-27 |
| 274 | Video Anomaly Detection Via Prediction Network with Enhanced Spatio-Temporal Memory Exchange Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Many approaches investigate the reconstruction difference between normal and abnormal patterns, but neglect that anomalies do not necessarily correspond to large reconstruction errors. To address this issue, we design a Convolutional LSTM Auto-Encoder prediction framework with enhanced spatio-temporal memory exchange using bi-directionalilty and a higher-order mechanism. |
Guodong Shen; Yuqi Ouyang; Victor Sanchez; | arxiv-cs.CV | 2022-06-26 |
| 275 | Self-Supervised Training with Autoencoders for Visual Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, neither of these techniques does explicitly penalise reconstruction of anomalous signals often resulting in a poor detection. We tackle this problem by adapting a self-supervised learning regime which allows to use discriminative information during training while regularising the model to focus on the data manifold by means of a modified reconstruction error resulting in an accurate detection. |
Alexander Bauer; | arxiv-cs.CV | 2022-06-23 |
| 276 | Human-AI Communication for Human-human Communication: Applying Interpretable Unsupervised Anomaly Detection to Executive Coaching Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we discuss the potential of applying unsupervised anomaly detection in constructing AI-based interactive systems that deal with highly contextual situations, i.e., human-human communication, in collaboration with domain experts. |
Riku Arakawa; Hiromu Yakura; | arxiv-cs.HC | 2022-06-22 |
| 277 | Can Process Mining Help in Anomaly-based Intrusion Detection? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider the naive applications of process mining in network traffic comprehension, traffic anomaly detection, and intrusion detection. |
Yinzheng Zhong; Alexei Lisitsa; | arxiv-cs.CR | 2022-06-21 |
| 278 | R2-AD2: Detecting Anomalies By Analysing The Raw Gradient Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Samples unlike the ones seen during training cause a different gradient distribution. Based on this intuition, we design a novel semi-supervised anomaly detection method called R2-AD2. |
Jan-Philipp Schulze; Philip Sperl; Ana Răduţoiu; Carla Sagebiel; Konstantin Böttinger; | arxiv-cs.LG | 2022-06-21 |
| 279 | Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: As an essential task in computer vision, video anomaly detection technology is used in video surveillance, scene understanding, road traffic analysis and other fields. However, … |
Bokun Wang; Caiqian Yang; | Sensors (Basel, Switzerland) | 2022-06-20 |
| 280 | ADBench: Anomaly Detection Benchmark Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and (iii) noisy and corrupted data? In this work, we answer these key questions by conducting (to our best knowledge) the most comprehensive anomaly detection benchmark with 30 algorithms on 57 benchmark datasets, named ADBench. |
Songqiao Han; Xiyang Hu; Hailiang Huang; Mingqi Jiang; Yue Zhao; | arxiv-cs.LG | 2022-06-19 |
| 281 | Multi-Contextual Predictions with Vision Transformer for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, to fully exploit the context information for anomaly detection in video circumstances, we designed the transformer model with three different contextual prediction streams: masked, whole and partial. |
Joo-Yeon Lee; Woo-Jeoung Nam; Seong-Whan Lee; | arxiv-cs.CV | 2022-06-17 |
| 282 | Detection and Quantification of Anomalies in Communication Networks Based on LSTM-ARIMA Combined Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The anomaly detection for communication networks is significant for improve the quality of communication services and network reliability. However, traditional communication … |
Sheng Xue; Hualiang Chen; Xiaoliang Zheng; | International journal of machine learning and cybernetics | 2022-06-17 |
| 283 | Deep Generative Model Using Unregularized Score for Anomaly Detection With Heterogeneous Complexity Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Accurate and automated detection of anomalous samples in an image dataset can be accomplished with a probabilistic model. Such images have heterogeneous complexity, however, and a probabilistic model tends to overlook simply shaped objects with small anomalies. |
Takashi Matsubara; Kazuki Sato; Kenta Hama; Ryosuke Tachibana; Kuniaki Uehara; | IEEE transactions on cybernetics | 2022-06-16 |
| 284 | Convolutional Recurrent Reconstructive Network for Spatiotemporal Anomaly Detection in Solder Paste Inspection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose a convolutional recurrent reconstructive network (CRRN), which decomposes the anomaly patterns generated by the printer defects, from SPI data. |
Yong-Ho Yoo; Ue-Hwan Kim; Jong-Hwan Kim; | IEEE transactions on cybernetics | 2022-06-16 |
| 285 | Hierarchical Conditional Variational Autoencoder Based Acoustic Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Different models have to be trained for each different kind of machines to accurately perform the anomaly detection task. To solve this issue, we propose a new method named as hierarchical conditional variational autoencoder (HCVAE). |
Harsh Purohit; Takashi Endo; Masaaki Yamamoto; Yohei Kawaguchi; | arxiv-cs.LG | 2022-06-11 |
| 286 | DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the growing diversity of cyberattacks in recent years, anomaly-based intrusion detection systems that can detect unknown attacks have attracted significant attention. … |
Naoto Yoshimura; Hiroki Kuzuno; Yoshiaki Shiraishi; Masakatu Morii; | Sensors (Basel, Switzerland) | 2022-06-10 |
| 287 | CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Thus, we propose Coupled-hypersphere-based Feature Adaptation (CFA) which accomplishes sophisticated anomaly localization using features adapted to the target dataset. |
Sungwook Lee; Seunghyun Lee; Byung Cheol Song; | arxiv-cs.CV | 2022-06-09 |
| 288 | Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose a novel strategy, Dual-distribution Discrepancy for Anomaly Detection (DDAD), utilizing both known normal images and unlabeled images. |
Yu Cai; Hao Chen; Xin Yang; Yu Zhou; Kwang-Ting Cheng; | arxiv-eess.IV | 2022-06-08 |
| 289 | A Comprehensive Survey of Graph-based Deep Learning Approaches for Anomaly Detection in Complex Distributed Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we explore the significant potential of graph-based algorithms to identify and mitigate different types of anomalies in complex distributed heterogeneous systems. |
ARMIN DANESH PAZHO et. al. | arxiv-cs.LG | 2022-06-08 |
| 290 | Catching Both Gray and Black Swans: Open-Set Supervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose a novel approach that learns disentangled representations of abnormalities illustrated by seen anomalies, pseudo anomalies, and latent residual anomalies (i.e., samples that have unusual residuals compared to the normal data in a latent space), with the last two abnormalities designed to detect unseen anomalies. |
Choubo Ding; Guansong Pang; Chunhua Shen; | cvpr | 2022-06-07 |
| 291 | Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Different from related methods, we propose to integrate the reconstruction-based functionality into a novel self-supervised predictive architectural building block. |
NICOLAE-CĂTĂLIN RISTEA et. al. | cvpr | 2022-06-07 |
| 292 | Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose to conduct novel Bayesian non-parametric submodular video partition (BN-SVP) to significantly improve MIL model training that can offer a highly reliable solution for robust anomaly detection in practical settings that include outlier segments or multiple types of abnormal events. |
Hitesh Sapkota; Qi Yu; | cvpr | 2022-06-07 |
| 293 | Generative Cooperative Learning for Unsupervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This problem is challenging yet rewarding as it can completely eradicate the costs of obtaining laborious annotations and enable such systems to be deployed without human intervention. To this end, we propose a novel unsupervised Generative Cooperative Learning (GCL) approach for video anomaly detection that exploits the low frequency of anomalies towards building a cross-supervision between a generator and a discriminator. |
M. ZAIGHAM ZAHEER et. al. | cvpr | 2022-06-07 |
| 294 | UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This is a closed-set scenario that fails to test the capability of systems at detecting new anomaly types. To this end, we propose UBnormal, a new supervised open-set benchmark composed of multiple virtual scenes for video anomaly detection. |
ANDRA ACSINTOAE et. al. | cvpr | 2022-06-07 |
| 295 | Anomaly Detection Via Reverse Distillation From One-Class Embedding Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: However, using similar or identical architectures to build the teacher and student models in previous studies hinders the diversity of anomalous representations. To tackle this problem, we propose a novel T-S model consisting of a teacher encoder and a student decoder and introduce a simple yet effective "reverse distillation" paradigm accordingly. |
Hanqiu Deng; Xingyu Li; | cvpr | 2022-06-07 |
| 296 | Anomaly Detection for Internet of Things Time Series Data Using Generative Adversarial Networks With Attention Mechanism in Smart Agriculture Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: More recently, smart agriculture has received widespread attention, which is a deep combination of modern agriculture and the Internet of Things (IoT) technology. To achieve the … |
Weijun Cheng; Tengfei Ma; Xiaoting Wang; Gang Wang; | Frontiers in plant science | 2022-06-06 |
| 297 | Anomaly Detection with Test Time Augmentation and Consistency Evaluation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple, yet effective post-hoc anomaly detection algorithm named Test Time Augmentation Anomaly Detection (TTA-AD), inspired by a novel observation. |
Haowei He; Jiaye Teng; Yang Yuan; | arxiv-cs.CV | 2022-06-06 |
| 298 | CAINNFlow: Convolutional Block Attention Modules and Invertible Neural Networks Flow for Anomaly Detection and Localization Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to retain and effectively extract spatial structure information, we design in this study a complex function model with alternating CBAM embedded in a stacked $3\times3$ full convolution, which is able to retain and effectively extract spatial structure information in the normalized flow model. |
RUIQING YAN et. al. | arxiv-cs.CV | 2022-06-04 |
| 299 | Anomaly Detection in Surveillance Videos Using Transformer Based Attention Model Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Therefore it is important to extract better quality features from the available videos. WIth this motivation, the present paper uses better quality transformer-based features named Videoswin Features followed by the attention layer based on dilated convolution and self attention to capture long and short range dependencies in temporal domain. |
Kapil Deshpande; Narinder Singh Punn; Sanjay Kumar Sonbhadra; Sonali Agarwal; | arxiv-cs.CV | 2022-06-03 |
| 300 | Are Smart Homes Adequate for Older Adults with Dementia? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Smart home technologies can enable older adults, including those with dementia, to live more independently in their homes for a longer time. Activity recognition, in combination … |
Gibson Chimamiwa; Alberto Giaretta; Marjan Alirezaie; Federico Pecora; Amy Loutfi; | Sensors (Basel, Switzerland) | 2022-06-02 |
| 301 | Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Second, the criteria of traffic anomalies may vary with locations and times. In this article, we propose a spatiotemporal graph convolutional adversarial network (STGAN) to address these above challenges. |
Leyan Deng; Defu Lian; Zhenya Huang; Enhong Chen; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 302 | Detecting Absence of Bone Wall in Jugular Bulb By Image Transformation Surrogate Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an anomaly detection method via image transformation surrogate tasks and apply it to detect the absence of bone wall in jugular bulb of temporal bone CT images. |
XIAOGUANG LI et. al. | IEEE transactions on medical imaging | 2022-06-01 |
| 303 | A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose a synergistic approach that leverages pattern mining to inform the GNN algorithms on how to aggregate local information through connections to capture the global patterns. |
Tong Zhao; Tianwen Jiang; Neil Shah; Meng Jiang; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 304 | Robust Unsupervised Video Anomaly Detection By Multipath Frame Prediction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we propose a novel and robust unsupervised video anomaly detection method by frame prediction with a proper design which is more in line with the characteristics of surveillance videos. |
XUANZHAO WANG et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 305 | Proximally Sensitive Error for Anomaly Detection and Feature Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Proximally Sensitive Error (PSE), through which we suggest that a regional emphasis in the error measure can ‘highlight’ semantic differences between images over syntactic/random deviations. |
Amogh Gudi; Fritjof Büttner; Jan van Gemert; | arxiv-cs.CV | 2022-06-01 |
| 306 | Deep Graph Learning for Anomalous Citation Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is one of the most active research areas in various critical domains, such as healthcare, fintech, and public security. However, little attention has been paid … |
Jiaying Liu; Feng Xia; Xu Feng; Jing Ren; Huan Liu; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 307 | Cross-Domain Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we aim to tackle the problem of cross-domain graph anomaly detection with domain adaptation. |
Kaize Ding; Kai Shu; Xuan Shan; Jundong Li; Huan Liu; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 308 | Memory-Augmented Generative Adversarial Networks for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: We propose a memory-augmented deep learning model for semisupervised anomaly detection (AD). While many traditional AD methods focus on modeling the distribution of normal data, … |
Ziyi Yang; Teng Zhang; Iman Soltani Bozchalooi; Eric Darve; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 309 | Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abnormal behaviors in industrial systems may be early warnings on critical events that may cause severe damages to facilities and security. Thus, it is important to detect … |
Qin Xie; Peng Zhang; Boseon Yu; Jaesik Choi; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 310 | Anomaly Detection on Attributed Networks Via Contrastive Self-Supervised Learning IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Furthermore, these methods do not directly target anomaly detection in their learning objective and fail to scale to large networks due to the full graph training mechanism. To overcome these limitations, in this article, we present a novel Contrastive self-supervised Learning framework for Anomaly detection on attributed networks (CoLA for abbreviation). |
YIXIN LIU et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 311 | Automated Anomaly Detection Via Curiosity-Guided Search and Self-Imitation Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is an important data mining task with numerous applications, such as intrusion detection, credit card fraud detection, and video surveillance. However, given a … |
YUENING LI et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 312 | Memorizing Structure-Texture Correspondence for Image Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: This work focuses on image anomaly detection by leveraging only normal images in the training phase. Most previous methods tackle anomaly detection by reconstructing the input … |
KANG ZHOU et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 313 | SmithNet: Strictness on Motion-Texture Coherence for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a convolutional neural network (CNN) that supports the detection of anomaly, which has not been defined when building the model, at frame level. |
Trong-Nguyen Nguyen; Sebastien Roy; Jean Meunier; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 314 | An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Abstract: Several techniques for multivariate time series anomaly detection have been proposed recently, but a systematic comparison on a common set of datasets and metrics is lacking. This … |
Astha Garg; Wenyu Zhang; Jules Samaran; Ramasamy Savitha; Chuan-Sheng Foo; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 315 | Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, due to the limited number of annotated anomaly samples, directly training networks with the discriminative loss may not be sufficient. To overcome this issue, this article proposes a novel strategy to transform the input data into a more meaningful representation that could be used for anomaly detection. |
YINGJIE ZHOU et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 316 | Center-Aware Adversarial Autoencoder for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In such cases, it is difficult to isolate the normal areas from the anomaly ones by making the subspace compact. To this end, we propose a center-aware adversarial autoencoder (CA-AAE) method, which detects anomaly samples by acquiring more compact and discriminative subspace representations. |
Daoming Li; Qinghua Tao; Jiahao Liu; Huangang Wang; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 317 | MAD-EN: Microarchitectural Attack Detection Through System-wide Energy Consumption Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this study, we introduce MAD-EN dynamic detection tool that leverages system-wide energy consumption traces collected from a generic Intel RAPL tool to detect ongoing anomalies in a system. |
Debopriya Roy Dipta; Berk Gulmezoglu; | arxiv-cs.CR | 2022-05-31 |
| 318 | Correlation-Based Anomaly Detection Method for Multi-sensor System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In industry, sensor-based monitoring of equipment or environment has become a necessity. Instead of using a single sensor, multi-sensor system is used to fully detect … |
HAN LI et. al. | Computational intelligence and neuroscience | 2022-05-31 |
| 319 | Benchmarking Unsupervised Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper extensively compares 13 papers in terms of the performance in unsupervised anomaly detection and localization tasks, and adds a comparison of inference efficiency previously ignored by the community. |
Ye Zheng; Xiang Wang; Yu Qi; Wei Li; Liwei Wu; | arxiv-cs.CV | 2022-05-30 |
| 320 | Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we explore the capabilities of the Hierarchical Temporal Memory (HTM) algorithm to perform anomaly detection in videos, as it has favorable properties such as noise tolerance and online learning which combats concept drift. |
Vladimir Monakhov; Vajira Thambawita; Pål Halvorsen; Michael A. Riegler; | arxiv-cs.CV | 2022-05-30 |
| 321 | Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we identify one reason that hinders most existing DNN-based anomaly detection methods from performing is the wide adoption of the Empirical Risk Minimization (ERM). |
Shaoshen Wang; Yanbin Liu; Ling Chen; Chengqi Zhang; | arxiv-cs.LG | 2022-05-29 |
| 322 | GTAD: Graph and Temporal Neural Network for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The rapid development of smart factories, combined with the increasing complexity of production equipment, has resulted in a large number of multivariate time series that can be … |
Siwei Guan; Binjie Zhao; Zhekang Dong; Mingyu Gao; Zhiwei He; | Entropy (Basel, Switzerland) | 2022-05-27 |
| 323 | Ensemble2: Anomaly Detection Via EVT-Ensemble Framework for Seasonal KPIs in Communication Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Traditional methods either require prior knowledge or manually set thresholds. To overcome these shortcomings, we propose the Ensemble2 framework, which applies ensemble learning to improve exogenous capabilities. |
Shi-Yang Wang; | arxiv-cs.LG | 2022-05-27 |
| 324 | FadMan: Federated Anomaly Detection Across Multiple Attributed Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the second scenario, by analyzing the distribution of abnormal nodes, we find that the nodes of traffic anomalies are associated with the event of postgraduate entrance examination on the same day. |
Nannan Wu; Ning Zhang; Wenjun Wang; Lixin Fan; Qiang Yang; | arxiv-cs.LG | 2022-05-27 |
| 325 | Multiscale Generative Model Using Regularized Skip-connections and Perceptual Loss for Anomaly Detection in Toxicologic Histopathology Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Automated anomaly detection is an important tool that has been developed for many real-world applications, including security systems, industrial inspection, and medical … |
Philip Zehnder; Jeffrey Feng; Reina N Fuji; Ruth Sullivan; Fangyao Hu; | Journal of pathology informatics | 2022-05-26 |
| 326 | Spatio-temporal Prediction and Reconstruction Network for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The existing anomaly detection methods can be divided into two popular models based on reconstruction or future frame prediction. Due to the strong learning capacity, … |
Ting Liu; Chengqing Zhang; Xiaodong Niu; Liming Wang; | PloS one | 2022-05-26 |
| 327 | Metric Learning-Based Fault Diagnosis and Anomaly Detection for Industrial Data With Intraclass Variance Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Besides, the actual system often operates in varying working conditions and is disturbed by the noise, which results in the intraclass variance of the raw data and degrades the performance of industrial system monitoring. To solve these problems, a metric learning-based fault diagnosis and anomaly detection method is proposed. |
Keke Huang; Shujie Wu; Bei Sun; Chunhua Yang; Weihua Gui; | IEEE transactions on neural networks and learning systems | 2022-05-24 |
| 328 | Learning Tensor Low-Rank Representation for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, existing LRR models generally convert 3-D hyperspectral images (HSIs) into 2-D matrices, inevitably leading to the destruction of intrinsic 3-D structure properties in HSIs. To this end, we propose a novel tensor low-rank and sparse representation (TLRSR) method for hyperspectral anomaly detection. |
Minghua Wang; Qiang Wang; Danfeng Hong; Swalpa Kumar Roy; Jocelyn Chanussot; | IEEE transactions on cybernetics | 2022-05-24 |
| 329 | Detecting Cyberattacks on Electrical Storage Systems Through Neural Network Based Anomaly Detection Algorithm Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the … |
GIOVANNI BATTISTA GAGGERO et. al. | Sensors (Basel, Switzerland) | 2022-05-23 |
| 330 | Detection of Fights in Videos: A Comparison Study of Anomaly Detection and Action Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Most existing methods use supervised binary action recognition. |
Weijun Tan; Jingfeng Liu; | arxiv-cs.CV | 2022-05-23 |
| 331 | MOSPAT: AutoML Based Model Selection and Parameter Tuning for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we explore MOSPAT, an end-to-end automated machine learning based approach for model and parameter selection, combined with a generative model to produce labeled data. |
Sourav Chatterjee; Rohan Bopardikar; Marius Guerard; Uttam Thakore; Xiaodong Jiang; | arxiv-cs.LG | 2022-05-23 |
| 332 | An Innovative Huffman Forest-Based Method to Detected Railroad Station Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Detecting railroad station anomalies is a critical task prior to segmentation and making optimization decisions for each cluster. Three types of anomalies (local clustered, axis … |
Yuan Wang; Xiaopeng Li; | Sensors (Basel, Switzerland) | 2022-05-22 |
| 333 | Learning Task-Specific Representation for Video Anomaly Detection with Spatial-Temporal Attention Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a spatial-temporal attention mechanism to learn inter- and intra-correlations of video clips, and the boosted features are encouraged to be task-specific via the mutual cosine embedding loss. |
Y. LIU et. al. | icassp | 2022-05-22 |
| 334 | PIXAL: Anomaly Reasoning with Visual Analytics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present PIXAL, a visual analytics system developed following an iterative design process with professional analysts responsible for anomaly detection. |
Brian Montambault; Camelia D. Brumar; Michael Behrisch; Remco Chang; | arxiv-cs.HC | 2022-05-22 |
| 335 | Controlled Sensing and Anomaly Detection Via Soft Actor-Critic Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the anomaly detection problem in the presence of noisy observations and to tackle the tuning and efficient exploration challenges that arise in deep reinforcement learning algorithms, we in this paper propose a soft actor-critic deep reinforcement learning framework. |
C. Zhong; M. C. Gursoy; S. Velipasalar; | icassp | 2022-05-22 |
| 336 | A Closer Look at Autoencoders for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Consequently, our exposition in this paper is to investigate the extent to which different latent space attributes of AEs impact their performances for anomaly detection tasks. |
O. K. Oyedotun; D. Aouada; | icassp | 2022-05-22 |
| 337 | Video Anomaly Detection Via Prediction Network with Enhanced Spatio-Temporal Memory Exchange Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Many approaches investigate the reconstruction difference between normal and abnormal patterns, but neglect that anomalies do not necessarily correspond to large reconstruction errors. To address this issue, we design a Convolutional LSTM Auto-Encoder prediction framework with enhanced spatiotemporal memory exchange using bi-directionalilty and a higher-order mechanism. |
G. Shen; Y. Ouyang; V. Sanchez; | icassp | 2022-05-22 |
| 338 | Stgat-Mad : Spatial-Temporal Graph Attention Network For Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel unsupervised multi-scale stacked spatial-temporal graph attention network for multivariate time series anomaly detection (STGAT-MAD). |
J. Zhan; et al. | icassp | 2022-05-22 |
| 339 | Approaches Toward Physical and General Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We introduce the Physical Anomalous Trajectory or Motion (PHANTOM) dataset 1, which contains six different video classes. |
L. Kart; N. Cohen; | icassp | 2022-05-22 |
| 340 | Unsupervised Anomaly Detection for Container Cloud Via BILSTM-Based Variational Auto-Encoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a real-time unsupervised anomaly detection system for monitoring system calls in container cloud via BiLSTM-based variational auto-encoder (VAE). |
Y. Wang; X. Chen; Q. Wang; R. Yang; B. Xin; | icassp | 2022-05-22 |
| 341 | Improving Anomaly Detection with A Self-Supervised Task Based on Generative Adversarial Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We assume that the main reason is that these methods ignore the diversity of patterns in normal samples. To alleviate the above issue, this paper proposes a novel anomaly detection framework based on generative adversarial network, called ADe-GAN. |
H. CHAI et. al. | icassp | 2022-05-22 |
| 342 | An Anomaly Detection Method Based on Self-Supervised Learning with Soft Label Assignment for Defect Visual Inspection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The reason is that the conventional method to generate labels ignores the differences of images between before and after the transformation. To address this issue, we propose soft label assignment (SLA) to construct soft labels via measuring the similarity between the original and transformed images. |
C. Hu; Y. Wang; | icassp | 2022-05-22 |
| 343 | Self-Supervised Acoustic Anomaly Detection Via Contrastive Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an acoustic anomaly detection algorithm based on the framework of contrastive learning. |
H. Hojjati; N. Armanfard; | icassp | 2022-05-22 |
| 344 | Multiple Temporal Context Embedding Networks for Unsupervised Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, various patterns of anomalous data, especially those lasting for varying periods, are hard to be captured by plain networks. To tackle this problem, we propose a multiple temporal context embedding method. |
H. Li; X. Peng; H. Zhuang; Z. Lin; | icassp | 2022-05-22 |
| 345 | Self-supervised Anomaly Detection for New Physics Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We investigate a method of model-agnostic anomaly detection through studying jets, collimated sprays of particles produced in high-energy collisions. |
Barry M. Dillon; Radha Mastandrea; Benjamin Nachman; | arxiv-hep-ph | 2022-05-20 |
| 346 | Detection of Mechanical Failures in Industrial Machines Using Overlapping Acoustic Anomalies: A Systematic Literature Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: One of the most important strategies for preventative factory maintenance is anomaly detection without the need for dedicated sensors for each industrial unit. The implementation … |
Ahmad Qurthobi; Rytis Maskeliūnas; Robertas Damaševičius; | Sensors (Basel, Switzerland) | 2022-05-20 |
| 347 | Time Series Anomaly Detection Via Reinforcement Learning-Based Model Selection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, to harness the benefits of different base models, we propose a reinforcement learning-based model selection framework. |
Jiuqi Elise Zhang; Di Wu; Benoit Boulet; | arxiv-cs.LG | 2022-05-19 |
| 348 | Anomaly Detection for Multivariate Time Series on Large-scale Fluid Handling Plant Using Two-stage Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, considering the complex behavior of high-dimensional signals and the demand for interpretability, the techniques constitute a major challenge. We introduce a Two-Stage AutoEncoder (TSAE) as an anomaly detection method suitable for such plants. |
Susumu Naito; Yasunori Taguchi; Kouta Nakata; Yuichi Kato; | arxiv-cs.LG | 2022-05-19 |
| 349 | Anomaly Detection Using Prediction Error with Spatio-Temporal Convolutional LSTM Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose a novel method for video anomaly detection motivated by an existing architecture for sequence-to-sequence prediction and reconstruction using a spatio-temporal convolutional Long Short-Term Memory (convLSTM). |
Hanh Thi Minh Tran; David Hogg; | arxiv-cs.CV | 2022-05-18 |
| 350 | Federated Anomaly Detection Over Distributed Data Streams Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an approach to building the bridge among anomaly detection, federated learning, and data streams. |
Paula Raissa Silva; João Vinagre; João Gama; | arxiv-cs.LG | 2022-05-16 |
| 351 | Unsupervised Abnormal Traffic Detection Through Topological Flow Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: By viewing network flows as weighted directed interactions between a pair of nodes, in this paper we present a simple method that facilitate the use of connectivity graph features in unsupervised anomaly detection algorithms. |
Paul Irofti; Andrei Pătraşcu; Andrei Iulian Hîji; | arxiv-cs.LG | 2022-05-14 |
| 352 | A Vision Inspired Neural Network for Unsupervised Anomaly Detection in Unordered Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Both the network and neuron display properties observed in biological processes including: immediate intelligence; parallel processing; redundancy; global degradation; contrast invariance; parameter-free computation, dynamic thresholds and non-linear processing. A robust and accurate model for anomaly detection in univariate and multivariate data is built using this network as a concrete application. |
Nassir Mohammad; | arxiv-cs.LG | 2022-05-13 |
| 353 | Self-Supervised Masking for Unsupervised Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To extend the reconstruction-based anomaly detection architecture to the localized anomalies, we propose a self-supervised learning approach through random masking and then restoring, named Self-Supervised Masking (SSM) for unsupervised anomaly detection and localization. |
Chaoqin Huang; Qinwei Xu; Yanfeng Wang; Yu Wang; Ya Zhang; | arxiv-cs.CV | 2022-05-13 |
| 354 | Anomaly Detection and Community Detection in Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Among the many well-known models for networks, latent variable models – a class of probabilistic models – offer promising tools to capture the intrinsic features of the data. In this work, we propose a probabilistic generative approach that incorporates domain knowledge, i.e., community membership, as a fundamental model for regular behavior, and thus flags potential anomalies deviating from this pattern. |
Hadiseh Safdari; Caterina De Bacco; | arxiv-cs.SI | 2022-05-12 |
| 355 | Deep Learning for Prawn Farming: Forecasting and Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a decision support system for managing water quality in prawn ponds. |
Joel Janek Dabrowski; Ashfaqur Rahman; Andrew Hellicar; Mashud Rana; Stuart Arnold; | arxiv-cs.LG | 2022-05-12 |
| 356 | Self-Supervised Anomaly Detection: A Survey and Outlook Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper aims to review the current approaches in self-supervised anomaly detection. |
Hadi Hojjati; Thi Kieu Khanh Ho; Narges Armanfard; | arxiv-cs.LG | 2022-05-10 |
| 357 | Deep Federated Anomaly Detection for Multivariate Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the problem of federated unsupervised anomaly detection and present a Federated Exemplar-based Deep Neural Network (Fed-ExDNN) to conduct anomaly detection for multivariate time series data on different edge devices. |
WEI ZHU et. al. | arxiv-cs.LG | 2022-05-09 |
| 358 | Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present an SSL-based model that enables anatomical structure-based unsupervised anomaly detection (UAD). |
JUNYA SATO et. al. | arxiv-cs.CV | 2022-05-09 |
| 359 | Spatiotemporal Consistency-enhanced Network for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Yi Hao; Jie Li; Nannan Wang; Xiaoyu Wang; Xinbo Gao; | Pattern Recognit. | |
| 360 | Network Traffic Anomaly Detection Method Based on Multi Scale Residual Feature Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the problem that traditional network traffic anomaly detection algorithms do not suffi-ciently mine potential features in long time domain, an anomaly detection method based on mul-ti-scale residual features of network traffic is proposed. |
Xueyuan Duan; Yu Fu; Kun Wang; | arxiv-cs.NI | 2022-05-08 |
| 361 | A Hybrid Approach: Utilising Kmeans Clustering and Naive Bayes for IoT Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The correct indentification percentage scores for this proposed algorithm range anywhere from 90% to 100%, as well as rating the proposed algorithms accuracy, precision and recall. These high scores achieve an accurate, flexible, scalable, optimised algorithm that could potentially be in different IoT devices, ensuring strong data integrity and privacy. |
Lincoln Best; Ernest Foo; Hui Tian; | arxiv-cs.CR | 2022-05-08 |
| 362 | MAD: Self-Supervised Masked Anomaly Detection Task for Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce Masked Anomaly Detection (MAD), a general self-supervised learning task for multivariate time series anomaly detection. |
Yiwei Fu; Feng Xue; | arxiv-cs.LG | 2022-05-04 |
| 363 | Unsupervised Brain Imaging 3D Anomaly Detection and Segmentation with Transformers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Pathological brain appearances may be so heterogeneous as to be intelligible only as anomalies, defined by their deviation from normality rather than any specific set of … |
WALTER H L PINAYA et. al. | Medical image analysis | 2022-05-04 |
| 364 | Detection Anomaly in Video Based on Deep Support Vector Data Description Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Video surveillance systems have been widely deployed in public places such as shopping malls, hospitals, banks, and streets to improve the safety of public life and assets. In … |
Bokun Wang; Caiqian Yang; Yaojing Chen; | Computational intelligence and neuroscience | 2022-05-04 |
| 365 | Object Class Aware Video Anomaly Detection Through Image Translation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: 2) Object-centric approaches neglect some of the context information (such as location). To tackle these challenges, this paper proposes a novel two-stream object-aware VAD method that learns the normal appearance and motion patterns through image translation tasks. |
Mohammad Baradaran; Robert Bergevin; | arxiv-cs.CV | 2022-05-03 |
| 366 | TracInAD: Measuring Influence for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel methodology to flag anomalies based on TracIn, an influence measure initially introduced for explicability purposes. |
Hugo Thimonier; Fabrice Popineau; Arpad Rimmel; Bich-Liên Doan; Fabrice Daniel; | arxiv-cs.LG | 2022-05-03 |
| 367 | ARCADE: Adversarially Regularized Convolutional Autoencoder for Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a practical unsupervised anomaly-based deep learning detection system called ARCADE (Adversarially Regularized Convolutional Autoencoder for unsupervised network anomaly DEtection). |
Willian T. Lunardi; Martin Andreoni Lopez; Jean-Pierre Giacalone; | arxiv-cs.LG | 2022-05-03 |
| 368 | Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a federated feature selection and feature reduction learning scheme is proposed to classify network traffic in a semi-supervised cooperative manner. |
Saira Bano; Achilles Machumilane; Lorenzo Valerio; Pietro Cassarà; Alberto Gotta; | arxiv-cs.LG | 2022-05-01 |
| 369 | MemStream: Memory-Based Streaming Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Thus, we need a data-efficient method that can detect and adapt to changing data trends, or concept drift, in an online manner. In this work, we propose MemStream, a streaming anomaly detection framework, allowing us to detect unusual events as they occur while being resilient to concept drift. |
Siddharth Bhatia; Arjit Jain; Shivin Srivastava; Kenji Kawaguchi; Bryan Hooi; | www | 2022-04-29 |
| 370 | A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Even though many anomaly detection techniques have been proposed, few of them can be directly applied to a given microservice or cloud server in industrial environment. To settle these challenges, this paper presents SLA-VAE, a semi-supervised learning based active anomaly detection framework using variational auto-encoder. |
Tao Huang; Pengfei Chen; Ruipeng Li; | www | 2022-04-29 |
| 371 | Robust System Instance Clustering for Large-Scale Web Services Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose OmniCluster to accurately and efficiently cluster system instances for large-scale Web services. |
SHENGLIN ZHANG et. al. | www | 2022-04-29 |
| 372 | A Novel Traffic Accident Detection Method with Comprehensive Traffic Flow Features Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the rapidly increasing of automobiles, traffic accidents are gradually becoming more frequent. This creates a great need for effective traffic anomaly detection algorithms. … |
Liping Zhu; Bingyao Wang; Yihan Yan; Shuang Guo; Gangyi Tian; | Signal, image and video processing | 2022-04-28 |
| 373 | Novel Applications for VAE-based Anomaly Detection Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we formulate a novel setting to deal with similar problems, showing that a repurposed anomaly detection system effectively generates novel data, avoiding generating specified unwanted data. |
Luca Bergamin; Tommaso Carraro; Mirko Polato; Fabio Aiolli; | arxiv-cs.LG | 2022-04-26 |
| 374 | IRC-safe Graph Autoencoder for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we construct an infrared and collinear safe autoencoder based on graph neural networks by employing energy-weighted message passing. |
OLIVER ATKINSON et. al. | arxiv-hep-ph | 2022-04-26 |
| 375 | Meta-Learning Based Early Fault Detection for Rolling Bearings Via Few-Shot Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The setting of EFD with limited target data considering UtUV can be formulated as a Few-shot Anomaly Detection task. Therefore, this paper proposes a novel EFD method based on meta-learning considering UtUV. |
Wenbin Song; Di Wu; Weiming Shen; Benoit Boulet; | arxiv-cs.LG | 2022-04-26 |
| 376 | A Survey on Unsupervised Visual Industrial Anomaly Detection Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we summarize current challenges and provide a thorough overview of recently proposed unsupervised algorithms for visual industrial anomaly detection covering five categories, whose innovation points and frameworks are described in detail. |
Yajie Cui; Zhaoxiang Liu; Shiguo Lian; | arxiv-cs.CV | 2022-04-23 |
| 377 | Discriminative Feature Learning Framework with Gradient Preference for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Extracting valuable feature vectors that can remarkably improve the performance of anomaly detection are essential in unsupervised representation learning. To this end, we propose a novel discriminative feature learning framework with gradient preference for anomaly detection. |
Muhao Xu; Xueying Zhou; Xizhan Gao; WeiKai He; Sijie Niu; | arxiv-cs.LG | 2022-04-23 |
| 378 | Hybrid Cloud-Edge Collaborative Data Anomaly Detection in Industrial Sensor Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering the limited availability of computing resources, this paper proposes a hybrid anomaly detection approach in cloud-edge collaboration industrial sensor networks. |
Tao Yang; Jinming Wang; Weijie Hao; Qiang Yang; Wenhai Wang; | arxiv-cs.CR | 2022-04-21 |
| 379 | Anomaly Detection of Calcifications in Mammography Based on 11,000 Negative Cases Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In mammography, calcifications are one of the most common signs of breast cancer. Detection of such lesions is an active area of research for computer-aided diagnosis and machine … |
RUI HOU et. al. | IEEE transactions on bio-medical engineering | 2022-04-21 |
| 380 | Feature Anomaly Detection System (FADS) for Intelligent Manufacturing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a simple new anomaly detection algorithm called FADS (feature-based anomaly detection system) which leverages pretrained convolutional neural networks (CNN) to generate a statistical model of nominal inputs by observing the activation of the convolutional filters. |
Anthony Garland; Kevin Potter; Matt Smith; | arxiv-cs.CV | 2022-04-21 |
| 381 | NLP Based Anomaly Detection for Categorical Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Few methods exist in the literature that address this task when some of the variables are categorical in nature. We formalize an analogy between categorical time series and classical Natural Language Processing and demonstrate the strength of this analogy for anomaly detection and root cause investigation by implementing and testing three different machine learning anomaly detection and root cause investigation models based upon it. |
Matthew Horak; Sowmya Chandrasekaran; Giovanni Tobar; | arxiv-cs.LG | 2022-04-21 |
| 382 | A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We extensively reviewed twelve of the most popular unsupervised anomaly detection methods. |
MAXIME ALVAREZ et. al. | arxiv-cs.LG | 2022-04-20 |
| 383 | Sintel: A Machine Learning Framework to Extract Insights from Signals Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we introduce Sintel, a machine learning framework for end-to-end time series tasks such as anomaly detection. |
Sarah Alnegheimish; Dongyu Liu; Carles Sala; Laure Berti-Equille; Kalyan Veeramachaneni; | arxiv-cs.LG | 2022-04-19 |
| 384 | Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents the preliminary results on evaluating the robustness of ML-based anomaly detection methods in safety-critical CPS against two types of accidental and malicious input perturbations, generated using a Gaussian-based noise model and the Fast Gradient Sign Method (FGSM). |
Xugui Zhou; Maxfield Kouzel; Homa Alemzadeh; | arxiv-cs.LG | 2022-04-19 |
| 385 | Flux+Mutability: A Conditional Generative Approach to One-Class Classification and Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe the possibility of dynamically generating a reference population and defining selection criteria via quantile cuts. |
C. Fanelli; J. Giroux; Z. Papandreou; | arxiv-cs.LG | 2022-04-18 |
| 386 | AFSC: Adaptive Fourier Space Compression for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose an Adaptive Fourier Space Compression (AFSC) module to distill healthy feature for AD. |
HAOTE XU et. al. | arxiv-eess.IV | 2022-04-17 |
| 387 | Anomaly Detection in Autonomous Driving: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This survey provides an extensive overview of anomaly detection techniques based on camera, lidar, radar, multimodal and abstract object level data. |
Daniel Bogdoll; Maximilian Nitsche; J. Marius Zöllner; | arxiv-cs.RO | 2022-04-17 |
| 388 | Anomalous Sound Detection Based on Machine Activity Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We have developed an unsupervised anomalous sound detection method for machine condition monitoring that utilizes an auxiliary task — detecting when the target machine is active. |
Tomoya Nishida; Kota Dohi; Takashi Endo; Masaaki Yamamoto; Yohei Kawaguchi; | arxiv-eess.AS | 2022-04-15 |
| 389 | LSTM-Autoencoder Based Anomaly Detection for Indoor Air Quality Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, traditional statistics and shallow machine learning-based approaches in anomaly detection in the IAQ area could not detect anomalies involving the observation of correlations across several data points (i.e., often referred to as long-term dependences). We propose a hybrid deep learning model that combines LSTM with Autoencoder for anomaly detection tasks in IAQ to address this issue. |
YUANYUAN WEI et. al. | arxiv-cs.LG | 2022-04-13 |
| 390 | Detecting Anomalous LAN Activities Under Differential Privacy Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present four approaches and show that they satisfy different levels of differential privacy – a rigorous and provable notion for quantifying privacy loss in a system. |
NORRATHEP RATTANAVIPANON et. al. | arxiv-cs.CR | 2022-04-13 |
| 391 | Epileptic Seizure Detection By Cascading Isolation Forest-Based Anomaly Screening and EasyEnsemble Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The electroencephalogram (EEG), for measuring the electrophysiological activity of the brain, has been widely applied in automatic detection of epilepsy seizures. Various … |
YAO GUO et. al. | IEEE transactions on neural systems and rehabilitation … | 2022-04-13 |
| 392 | Evaluation of Machine Learning Method for Intrusion Detection System on Jubatus Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: —The network intrusion is becoming a big threat for a lot of companies, organization and so on. Recent intrusions are becoming more clever and difficult to detect. Many of today’s … |
Tadashi Ogino; | ||
| 393 | Self-Supervised Losses for One-Class Textual Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study a simpler alternative: fine-tuning Transformers on the inlier data with self-supervised objectives and using the losses as an anomaly score. |
Kimberly T. Mai; Toby Davies; Lewis D. Griffin; | arxiv-cs.CL | 2022-04-12 |
| 394 | Unsupervised Anomaly Detection in 3D Brain MRI Using Deep Learning with Impured Training Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For our evaluations, we consider three publicly available data sets and use autoencoders (AE) as a well-established baseline method for UAD. |
FINN BEHRENDT et. al. | arxiv-eess.IV | 2022-04-12 |
| 395 | Unsupervised Anomaly and Change Detection with Multivariate Gaussianization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an unsupervised method for detecting anomalies and changes in remote sensing images by means of a multivariate Gaussianization methodology that allows to estimate multivariate densities accurately, a long-standing problem in statistics and machine learning. |
José A. Padrón-Hidalgo; Valero Laparra; Gustau Camps-Valls; | arxiv-cs.LG | 2022-04-12 |
| 396 | Unsupervised Multimodal Anomaly Detection With Missing Sources for Liquid Rocket Engine Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, current AD methods mainly aim at single source or single modality, whereas existing multimodal methods cannot effectively cope with a common issue, modality incompleteness. To this end, we propose an unsupervised multimodal method for AD with missing sources in LRE system. |
YONG FENG et. al. | IEEE transactions on neural networks and learning systems | 2022-04-12 |
| 397 | Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Heterogeneous cyberattacks against industrial control systems (ICSs) have had a strong impact on the physical world in recent decades. Connecting devices to the internet enables … |
Daniel Fährmann; Naser Damer; Florian Kirchbuchner; Arjan Kuijper; | Sensors (Basel, Switzerland) | 2022-04-09 |
| 398 | FamilyGuard: A Security Architecture for Anomaly Detection in Home Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The residential environment is constantly evolving technologically. With this evolution, sensors have become intelligent interconnecting home appliances, personal computers, and … |
Pedro H A D de Melo; Rodrigo Sanches Miani; Pedro Frosi Rosa; | Sensors (Basel, Switzerland) | 2022-04-09 |
| 399 | A Video Anomaly Detection Framework Based on Appearance-Motion Semantics Representation Consistency Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Anomalies only occur in the moving foreground of surveillance videos, so the semantics expressed by video frame sequences and optical flow without background information in anomaly detection should be highly consistent and significant for anomaly detection. Based on this idea, we propose Appearance-Motion Semantics Representation Consistency (AMSRC), a framework that uses normal data’s appearance and motion semantic representation consistency to handle anomaly detection. |
Xiangyu Huang; Caidan Zhao; Yilin Wang; Zhiqiang Wu; | arxiv-cs.CV | 2022-04-08 |
| 400 | EPASAD: Ellipsoid Decision Boundary Based Process-Aware Stealthy Attack Detector Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: PASAD is one example of anomaly detection in the sensor/actuator data, representing such systems’ physical dynamics. We present EPASAD, which improves the detection technique used in PASAD to detect these micro-stealthy attacks, as our experiments show that PASAD’s spherical boundary-based detection fails to detect. |
Vikas Maurya; Rachit Agarwal; Saurabh Kumar; Sandeep Kumar Shukla; | arxiv-cs.CR | 2022-04-08 |
| 401 | Adversarial Analysis of The Differentially-Private Federated Learning in Cyber-Physical Critical Infrastructures Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Nonetheless, very little effort has been made in the literature to investigate this adversarial exploitation of the DP-noise. To overcome this gap, in this paper, we present a novel adaptive model poisoning technique {\alpha}-MPELM} through which an attacker can exploit the additional DP-noise to evade the state-of-the-art anomaly detection techniques and prevent optimal convergence of the FL model. |
MD TAMJID HOSSAIN et. al. | arxiv-cs.CR | 2022-04-06 |
| 402 | Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Although adversarial attacks on image understanding models have been heavily investigated, there is not much work on adversarial machine learning targeting video understanding models and no previous work which focuses on video anomaly detection. To this end, we investigate an adversarial machine learning attack against video anomaly detection systems, that can be implemented via an easy-to-perform cyber-attack. |
Furkan Mumcu; Keval Doshi; Yasin Yilmaz; | arxiv-cs.CV | 2022-04-06 |
| 403 | PDNPulse: Sensing PCB Anomaly with The Intrinsic Power Delivery Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose PDNPulse, a power delivery network (PDN) based PCB anomaly detection framework that can identify a wide spectrum of board-level malicious modifications. |
HUIFENG ZHU et. al. | arxiv-cs.CR | 2022-04-05 |
| 404 | Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Grounded in the application of machine health monitoring, we propose a framework that adapts to new conditions with few-shot samples. |
Bingqing Chen; Luca Bondi; Samarjit Das; | arxiv-cs.SD | 2022-04-04 |
| 405 | Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the anomaly detection performance of sixteen conventional, machine learning-based and, deep neural network approaches on five real-world open datasets. |
Julien Audibert; Pietro Michiardi; Frédéric Guyard; Sébastien Marti; Maria A. Zuluaga; | arxiv-cs.LG | 2022-04-04 |
| 406 | Proactive Anomaly Detection for Robot Navigation with Multi-Sensor Fusion Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We propose a proactive anomaly detection network (PAAD) for robot navigation in unstructured and uncertain environments. |
Tianchen Ji; Arun Narenthiran Sivakumar; Girish Chowdhary; Katherine Driggs-Campbell; | arxiv-cs.RO | 2022-04-03 |
| 407 | Deep Learning-based Anomaly Detection from Ultrasonic Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Non-destructive testing is a group of methods for evaluating the integrity of components. Among them, ultrasonic inspection stands out due to its ability to visualize both shallow … |
LUKA POSILOVIĆ et. al. | Ultrasonics | 2022-04-02 |
| 408 | Privacy-preserving Anomaly Detection in Cloud Manufacturing Via Federated Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we introduce federated learning (FL) framework that allows edge devices to train an anomaly detection model in collaboration with the cloud without compromising privacy. |
SHIYAO MA et. al. | arxiv-cs.DC | 2022-04-02 |
| 409 | A Survey of Single-Scene Video Anomaly Detection IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: This article summarizes research trends on the topic of anomaly detection in video feeds of a single scene. We discuss the various problem formulations, publicly available … |
Bharathkumar Ramachandra; Michael J Jones; Ranga Raju Vatsavai; | IEEE transactions on pattern analysis and machine … | 2022-04-01 |
| 410 | Anomaly Detection Using Edge Computing in Video Surveillance System: Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The current concept of smart cities influences urban planners and researchers to provide modern, secured and sustainable infrastructure and gives a decent quality of life to its … |
Devashree R Patrikar; Mayur Rajaram Parate; | International journal of multimedia information retrieval | 2022-03-29 |
| 411 | Radial Autoencoders for Enhanced Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The new concept is studied here in relation with a schematic artificial dataset, and the derived methods show consistent score improvements. |
Mihai-Cezar Augustin; Vivien Bonvin; Regis Houssou; Efstratios Rappos; Stephan Robert-Nicoud; | arxiv-cs.LG | 2022-03-29 |
| 412 | Contextual Information Based Anomaly Detection for A Multi-Scene UAV Aerial Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this regard, the present work aims at the development of a Computer Aided Decision support system to analyse UAV based surveillance videos. |
Girisha S; Ujjwal Verma; Manohara Pai M M; Radhika M Pai; | arxiv-cs.CV | 2022-03-29 |
| 413 | Semi-supervised Anomaly Detection Algorithm Based on KL Divergence (SAD-KL) Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To deal the problem caused by distribution gap between labeled and unlabeled data, we propose a semi-supervised anomaly detection algorithm using KL divergence (SAD-KL). |
Chong Hyun Lee; Kibae Lee; | arxiv-cs.LG | 2022-03-28 |
| 414 | AnoDFDNet: A Deep Feature Difference Network for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper proposed a novel anomaly detection (AD) approach of High-speed Train images based on convolutional neural networks and the Vision Transformer. |
Zhixue Wang; Yu Zhang; Lin Luo; Nan Wang; | arxiv-cs.CV | 2022-03-28 |
| 415 | From MIM-Based GAN to Anomaly Detection:Event Probability Influence on Generative Adversarial Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the exponential information metric into the GAN, referred to as MIM-based GAN, whose superior characteristics on data generation are discussed in theory. |
Rui She; Pingyi Fan; | arxiv-cs.LG | 2022-03-25 |
| 416 | Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a weakly supervised anomaly detection system which has multiple contributions including a random batch selection mechanism to reduce inter-batch correlation and a normalcy suppression block which learns to minimize anomaly scores over normal regions of a video by utilizing the overall information available in a training batch. |
Muhammad Zaigham Zaheer; Arif Mahmood; Marcella Astrid; Seung-Ik Lee; | arxiv-cs.CV | 2022-03-25 |
| 417 | Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the current study, we propose a robust anomaly detection framework that overcomes such instability by transforming the fundamental role of the discriminator from identifying real vs. fake data to distinguishing good vs. bad quality reconstructions. |
Muhammad Zaigham Zaheer; Jin Ha Lee; Arif Mahmood; Marcella Astrid; Seung-Ik Lee; | arxiv-cs.CV | 2022-03-25 |
| 418 | SIFT and SURF Based Feature Extraction for The Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we suggest a way, how to use SIFT and SURF algorithms to extract the image features for anomaly detection. |
Simon Bilik; Karel Horak; | arxiv-cs.CV | 2022-03-24 |
| 419 | Domain-Generalized Textured Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the task of domain-generalized textured surface anomaly detection. |
Shang-Fu Chen; Yu-Min Liu; Chia-Ching Lin; Trista Pei-Chun Chen; Yu-Chiang Frank Wang; | arxiv-cs.CV | 2022-03-23 |
| 420 | Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we formulate polyp detection as a weakly-supervised anomaly detection task that uses video-level labelled training data to detect frame-level polyps. |
YU TIAN et. al. | arxiv-cs.CV | 2022-03-22 |
| 421 | Unsupervised Anomaly Detection in Medical Images with A Memory-augmented Multi-level Cross-attentional Masked Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we introduce a new reconstruction-based UAD approach that addresses this low-reconstruction error issue for anomalous images. |
YU TIAN et. al. | arxiv-eess.IV | 2022-03-22 |
| 422 | ASE: Anomaly Scoring Based Ensemble Learning for Imbalanced Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Existing models sometimes treat minority classes as noise or ignore them as outliers encountering data skewing. In order to solve this problem, we propose a bagging ensemble learning framework $ASE$ (Anomaly Scoring Based Ensemble Learning). |
Xiayu Liang; Ying Gao; Shanrong Xu; | arxiv-cs.LG | 2022-03-21 |
| 423 | Industrial Network-based Behavioral Anomaly Detection in AI-enabled Smart Manufacturing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Existing manufacturing systems are isolated from the outside world to protect their sites and systems. However, following the trend of the 4th Industrial Revolution, manufacturing … |
HyunJin Kim; Taeshik Shon; | The Journal of supercomputing | 2022-03-21 |
| 424 | Diverse Counterfactual Explanations for Anomaly Detection in Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a model-agnostic algorithm that generates counterfactual ensemble explanations for time series anomaly detection models. |
DEBORAH SULEM et. al. | arxiv-cs.LG | 2022-03-21 |
| 425 | AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-Decoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose a vision transformer-based encoder-decoder model, named AnoViT, designed to reflect normal information by additionally learning the global relationship between image patches, which is capable of both image anomaly detection and localization. |
Yunseung Lee; Pilsung Kang; | arxiv-cs.CV | 2022-03-21 |
| 426 | An End-to-end Computer Vision Methodology for Quantitative Metallography Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Abstract: Metallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the occurrence and characteristics … |
Matan Rusanovsky; Ofer Beeri; Gal Oren; | Scientific reports | 2022-03-21 |
| 427 | Anomaly Detection in Emails Using Machine Learning and Header Information Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To overcome this deficit, this study conducted feature extraction and selection on email header datasets and leveraged both multi and one-class anomaly detection approaches. |
Craig Beaman; Haruna Isah; | arxiv-cs.CR | 2022-03-19 |
| 428 | Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In addition, pursuing the coefficient matrix reinforced by the general $l_2$-min is very time consuming. To address these issues, a nonnegative-constrained joint collaborative representation model is proposed in this paper for the hyperspectral anomaly detection task. |
Shizhen Chang; Pedram Ghamisi; | arxiv-cs.CV | 2022-03-18 |
| 429 | Context-Dependent Anomaly Detection with Knowledge Graph Embedding Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we leverage contextual awareness for the anomaly detection problem. |
Nathan Vaska; Kevin Leahy; Victoria Helus; | arxiv-cs.LG | 2022-03-17 |
| 430 | The Analysis of Online Event Streams: Predicting The Next Activity for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose to tackle the online event anomaly detection problem using next-activity prediction methods. |
Suhwan Lee; Xixi Lu; Hajo A. Reijers; | arxiv-cs.LG | 2022-03-17 |
| 431 | Driving Anomaly Detection Using Conditional Generative Adversarial Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study proposes an unsupervised method to quantify driving anomalies using a conditional generative adversarial network (GAN). |
Yuning Qiu; Teruhisa Misu; Carlos Busso; | arxiv-cs.CV | 2022-03-15 |
| 432 | Practical Data Monitoring in The Internet-services Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper presents a framework for reliable large-scale anomaly detection. |
Nikhil Galagali; | arxiv-cs.LG | 2022-03-15 |
| 433 | Feature Space Reduction As Data Preprocessing for The Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present two pipelines in order to reduce the feature space for anomaly detection using the One Class SVM. |
Simon Bilik; Karel Horak; | arxiv-cs.CV | 2022-03-13 |
| 434 | LesionPaste: One-Shot Anomaly Detection for Medical Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a one-shot anomaly detection framework, namely LesionPaste, that utilizes true anomalies from a single annotated sample and synthesizes artificial anomalous samples for anomaly detection. |
Weikai Huang; Yijin Huang; Xiaoying Tang; | arxiv-eess.IV | 2022-03-12 |
| 435 | Back to The Feature: Classical 3D Features Are (Almost) All You Need for 3D Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This is counter-intuitive as even a simple inspection of the dataset shows that color-only methods are insufficient for images containing geometric anomalies. This motivates the question: how can anomaly detection methods effectively use 3D information? |
Eliahu Horwitz; Yedid Hoshen; | arxiv-cs.CV | 2022-03-10 |
| 436 | A Review of Open Source Software Tools for Time Series Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The goal of this paper is to provide a concise and user friendly overview of the most important open source tools for time series analysis. |
Yunus Parvej Faniband; Iskandar Ishak; Sadiq M. Sait; | arxiv-cs.LG | 2022-03-10 |
| 437 | TiSAT: Time Series Anomaly Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we propose a proper evaluation metric that measures the timeliness and precision of detecting sequential anomalies. |
Keval Doshi; Shatha Abudalou; Yasin Yilmaz; | arxiv-cs.LG | 2022-03-10 |
| 438 | Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using A Stacked Recurrent Autoencoder Method with Dynamic Thresholding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a system incorporating a Long Short-Term Memory (LSTM) Deep Learning Autoencoder based method with a novel dynamic thresholding algorithm and weighted loss function for anomaly detection of a UAV dataset, in order to contribute to the ongoing efforts that leverage innovations in machine learning and data analysis within the aviation industry. |
Victoria Bell1; Divish Rengasamy; Benjamin Rothwell; Grazziela P Figueredo; | arxiv-cs.LG | 2022-03-09 |
| 439 | Visual Anomaly Detection in Video By Variational Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we have demonstrated comparison between performance of convolutional LSTM versus a variation convolutional LSTM autoencoder |
Faraz Waseem; Rafael Perez Martinez; Chris Wu; | arxiv-cs.CV | 2022-03-08 |
| 440 | Diffusion Models for Medical Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present a novel weakly supervised anomaly detection method based on denoising diffusion implicit models. |
Julia Wolleb; Florentin Bieder; Robin Sandkühler; Philippe C. Cattin; | arxiv-eess.IV | 2022-03-08 |
| 441 | Generative Cooperative Learning for Unsupervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a novel unsupervised Generative Cooperative Learning (GCL) approach for video anomaly detection that exploits the low frequency of anomalies towards building a cross-supervision between a generator and a discriminator. |
MUHAMMAD ZAIGHAM ZAHEER et. al. | arxiv-cs.CV | 2022-03-08 |
| 442 | Machine Learning Based Anomaly Detection for Smart Shirt: A Systematic Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study presents a Systematic Review of the Literature (SLR) on Anomaly Detection usingML techniques in Smart Shirt. |
E. C. Nunes; | arxiv-cs.LG | 2022-03-07 |
| 443 | Object-centric and Memory-guided Normality Reconstruction for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Due to the inherent rarity and heterogeneity of abnormal events, the problem is viewed as a normality modeling strategy, in which our model learns object-centric normal patterns without seeing anomalous samples during training. |
KHALIL BERGAOUI et. al. | arxiv-cs.CV | 2022-03-07 |
| 444 | The Familiarity Hypothesis: Explaining The Behavior of Deep Open Set Methods Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For example when an image contains both a novel object and a familiar one, the familiarity score will be high, so the novel object will not be noticed. The paper reviews evidence from the literature and presents additional evidence from our own experiments that provide strong support for this hypothesis. |
Thomas G. Dietterich; Alexander Guyer; | arxiv-cs.CV | 2022-03-04 |
| 445 | Hyperspectral Anomaly Detection With Tensor Average Rank and Piecewise Smoothness Constraints Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in hyperspectral images (HSIs) has attracted considerable interest in the remote-sensing domain, which aims to identify pixels with different spectral and … |
Siyu Sun; Jun Liu; Xun Chen; Wei Li; Hongbin Li; | IEEE transactions on neural networks and learning systems | 2022-03-04 |
| 446 | Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper presents a full-stack deployment of an efficient and scalable anomaly detection pipeline for SHM systems which does not require sending raw data to the cloud but relies on edge computation. |
Amirhossein Moallemi; Alessio Burrello; Davide Brunelli; Luca Benini; | arxiv-cs.NI | 2022-03-04 |
| 447 | Data-Efficient and Interpretable Tabular Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel AD framework that adapts a white-box model class, Generalized Additive Models, to detect anomalies using a partial identification objective which naturally handles noisy or heterogeneous features. |
Chun-Hao Chang; Jinsung Yoon; Sercan Arik; Madeleine Udell; Tomas Pfister; | arxiv-cs.LG | 2022-03-03 |
| 448 | Anomaly Detection in Big Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our aim in the thesis is to tackle big data problems while detecting anomaly efficiently. |
Chandresh Kumar Maurya; | arxiv-cs.LG | 2022-03-03 |
| 449 | Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a fraud and abuse detection framework for streaming services by modeling user streaming behavior. |
Soheil Esmaeilzadeh; Negin Salajegheh; Amir Ziai; Jeff Boote; | arxiv-cs.LG | 2022-03-03 |
| 450 | Creating Simple, Interpretable Anomaly Detectors for New Physics in Jet Substructure Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose two different strategies that use a small number of high-level observables to mimic the decisions made by the autoencoder on background events, one designed to directly learn the output of the autoencoder, and the other designed to learn the difference between the autoencoder’s outputs on a pair of events. |
Layne Bradshaw; Spencer Chang; Bryan Ostdiek; | arxiv-hep-ph | 2022-03-02 |
| 451 | A Correlation-Based Anomaly Detection Model for Wireless Body Area Networks Using Convolutional Long Short-Term Memory Neural Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: As the Internet of Healthcare Things (IoHT) concept emerges today, Wireless Body Area Networks (WBAN) constitute one of the most prominent technologies for improving healthcare … |
Albatul Albattah; Murad A Rassam; | Sensors (Basel, Switzerland) | 2022-03-02 |
| 452 | Unsupervised Anomaly Detection from Time-of-Flight Depth Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We evaluate the application of existing autoencoder-based methods on depth video and propose how the advantages of using depth data can be leveraged by integration into the loss function. |
Pascal Schneider; Jason Rambach; Bruno Mirbach; Didier Stricker; | arxiv-cs.CV | 2022-03-02 |
| 453 | Proxy-Bridged Image Reconstruction Network for Anomaly Detection in Medical Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in medical images refers to the identification of abnormal images with only normal images in the training set. Most existing methods solve this problem with a … |
KANG ZHOU et. al. | IEEE transactions on medical imaging | 2022-03-02 |
| 454 | Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Concretely, we propose a Frequency Decoupling (FD) module to decouple the input image into different frequency components and model the reconstruction process as a combination of parallel omni-frequency image restorations, as we observe a significant difference in the frequency distribution of normal and abnormal images. |
YUFEI LIANG et. al. | arxiv-cs.CV | 2022-03-01 |
| 455 | DistAD: Software Anomaly Detection Based on Execution Trace Distribution Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel anomaly detection method named DistAD, which is based on the distribution of software runtime dynamic execution traces. |
Shiyi Kong; Jun Ai; Minyan Lu; Shuguang Wang; W. Eric Wong; | arxiv-cs.SE | 2022-02-28 |
| 456 | Prior-Based Tensor Approximation for Anomaly Detection in Hyperspectral Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The key to hyperspectral anomaly detection is to effectively distinguish anomalies from the background, especially in the case that background is complex and anomalies are weak. … |
LU LI et. al. | IEEE transactions on neural networks and learning systems | 2022-02-28 |
| 457 | Anomaly Detection With Bidirectional Consistency in Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The core component of most anomaly detectors is a self-supervised model, tasked with modeling patterns included in training samples and detecting unexpected patterns as the … |
Zhiwen Fang; Jiafei Liang; Joey Tianyi Zhou; Yang Xiao; Feng Yang; | IEEE transactions on neural networks and learning systems | 2022-02-28 |
| 458 | Improving Variational Autoencoders for New Physics Detection at The LHC With Normalizing Flows Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a … |
PRATIK JAWAHAR et. al. | Frontiers in big data | 2022-02-28 |
| 459 | Statistics and Deep Learning-based Hybrid Model for Interpretable Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, an extension of MES-LSTM is presented, an interpretable anomaly detection model that overcomes these challenges. |
Thabang Mathonsi; Terence L van Zyl; | arxiv-cs.LG | 2022-02-25 |
| 460 | Self-Supervised and Interpretable Anomaly Detection Using Network Transformers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the Network Transformer (NeT), a DNN model for anomaly detection that incorporates the graph structure of the communication network in order to improve interpretability. |
Daniel L. Marino; Chathurika S. Wickramasinghe; Craig Rieger; Milos Manic; | arxiv-cs.LG | 2022-02-25 |
| 461 | Data Refinement for Fully Unsupervised Visual Inspection Using Pre-trained Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: There exists to our knowledge no work studying these pre-trained methods under fully unsupervised setting. |
Antoine Cordier; Benjamin Missaoui; Pierre Gutierrez; | arxiv-cs.CV | 2022-02-25 |
| 462 | Bayesian Autoencoders with Uncertainty Quantification: Towards Trustworthy Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this work, the formulation of Bayesian autoencoders (BAEs) is adopted to quantify the total anomaly uncertainty, comprising epistemic and aleatoric uncertainties. |
Bang Xiang Yong; Alexandra Brintrup; | arxiv-cs.LG | 2022-02-25 |
| 463 | Do Autoencoders Need A Bottleneck for Anomaly Detection? Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we challenge this limiting belief and investigate the value of non-bottlenecked AEs. |
Bang Xiang Yong; Alexandra Brintrup; | arxiv-cs.LG | 2022-02-25 |
| 464 | Stacked Residuals of Dynamic Layers for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an end-to-end differentiable neural network architecture to perform anomaly detection in multivariate time series by incorporating a Sequential Probability Ratio Test on the prediction residual. |
L. Zancato; A. Achille; G. Paolini; A. Chiuso; S. Soatto; | arxiv-cs.LG | 2022-02-24 |
| 465 | Anomaly Detection in 3D Point Clouds Using Deep Geometric Descriptors Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new method for the unsupervised detection of geometric anomalies in high-resolution 3D point clouds. |
Paul Bergmann; David Sattlegger; | arxiv-cs.CV | 2022-02-23 |
| 466 | A Spectral-spatial Fusion Anomaly Detection Method for Hyperspectral Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a spectralspatial fusion anomaly detection (SSFAD) method is proposed for hyperspectral imagery. |
Zengfu Hou; Siyuan Cheng; Ting Hu; | arxiv-eess.IV | 2022-02-23 |
| 467 | Weighted IForest and Siamese GRU on Small Sample Anomaly Detection in Healthcare Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Background and objectiveAt present, many achievements have been made in anomaly detection of big data using deep neural network, However, in many practical application scenarios, … |
Junfeng Wang; Yan Jia; Dongbo Wang; Wenjing Xiao; Zhenfei Wang; | Computer methods and programs in biomedicine | 2022-02-23 |
| 468 | ML-based Anomaly Detection in Optical Fiber Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a data driven approach for the anomaly detection and faults identification in optical networks to diagnose physical attacks such as fiber breaks and optical tapping. |
Khouloud Abdelli; Joo Yeon Cho; Carsten Tropschug; | arxiv-cs.CR | 2022-02-23 |
| 469 | Recurrent Auto-Encoder With Multi-Resolution Ensemble and Predictive Coding for Multivariate Time-Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose an unsupervised multivariate time-series anomaly detection model named RAE-MEPC which learns informative normal representations based on multi-resolution ensemble and predictive coding. |
Heejeong Choi; Subin Kim; Pilsung Kang; | arxiv-cs.LG | 2022-02-21 |
| 470 | Anomaly Search Over Composite Hypotheses in Hierarchical Statistical Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider anomaly detection with observations taken from a chosen subset of processes that conforms to a predetermined tree structure with partially known statistical model. |
Benjamin Wolff; Tomer Gafni; Guy Revach; Nir Shlezinger; Kobi Cohen; | arxiv-cs.IT | 2022-02-21 |
| 471 | Application of Thermography and Adversarial Reconstruction Anomaly Detection in Power Cast-Resin Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Dry-type power transformers play a critical role in the power system. Detecting various overheating faults in the running state of the power transformer is necessary to avoid the … |
Kuo-Hao Fanchiang; Cheng-Chien Kuo; | Sensors (Basel, Switzerland) | 2022-02-17 |
| 472 | Anomalib: A Deep Learning Library for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This paper introduces anomalib, a novel library for unsupervised anomaly detection and localization. |
SAMET AKCAY et. al. | arxiv-cs.CV | 2022-02-16 |
| 473 | Deep Generative Model with Hierarchical Latent Factors for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This work presents DGHL, a new family of generative models for time series anomaly detection, trained by maximizing the observed likelihood by posterior sampling and alternating back-propagation. |
Cristian Challu; Peihong Jiang; Ying Nian Wu; Laurent Callot; | arxiv-cs.LG | 2022-02-15 |
| 474 | Deep Learning-based Anomaly Detection on X-ray Images of Fuel Cell Electrodes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this work, we created a real-world labeled anomaly dataset, consisting of 16-bit X-ray image data of fuel cell electrodes coated with a platinum catalyst solution and perform anomaly detection on the dataset using a deep learning approach. |
Simon B. Jensen; Thomas B. Moeslund; Søren J. Andreasen; | arxiv-cs.CV | 2022-02-15 |
| 475 | Trustworthy Anomaly Detection: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this brief survey, we summarize the existing efforts and discuss open problems towards trustworthy anomaly detection from the perspectives of interpretability, fairness, robustness, and privacy-preservation. |
Shuhan Yuan; Xintao Wu; | arxiv-cs.LG | 2022-02-15 |
| 476 | Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: A Bayesian network is a directed acyclic graph (DAG) that models causal relationships; it factorizes the joint probability of the series into the product of easy-to-evaluate conditional probabilities. We call such a graph-augmented normalizing flow approach GANF and propose joint estimation of the DAG with flow parameters. |
Enyan Dai; Jie Chen; | arxiv-cs.LG | 2022-02-15 |
| 477 | DeCorus: Hierarchical Multivariate Anomaly Detection at Cloud-Scale Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce our approach to hierarchical multivariate anomaly detection called DeCorus, a statistical multivariate anomaly detector which achieves linear complexity. |
BRUNO WASSERMANN et. al. | arxiv-cs.LG | 2022-02-14 |
| 478 | AnoMili: Spoofing Prevention and Explainable Anomaly Detection for The 1553 Military Avionic Bus Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the defense in depth principle, we propose AnoMili, a novel protection system for the MIL-STD-1553 bus, which consists of: (i) a physical intrusion detection mechanism that detects unauthorized devices connected to the 1553 bus, even if they are passive (sniffing), (ii) a device fingerprinting mechanism that protects against spoofing attacks (two approaches are proposed: prevention and detection), (iii) a context-based anomaly detection mechanism, and (iv) an anomaly explanation engine responsible for explaining the detected anomalies in real time. |
Efrat Levy; Nadav Maman; Asaf Shabtai; Yuval Elovici; | arxiv-cs.CR | 2022-02-14 |
| 479 | A Survey of Visual Sensory Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this survey, we are the first one to provide a comprehensive review of visual sensory AD and category into three levels according to the form of anomalies. |
XI JIANG et. al. | arxiv-cs.CV | 2022-02-14 |
| 480 | DoTA: Unsupervised Detection of Traffic Anomaly in Driving Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Video anomaly detection has been extensively studied for static cameras but is much more challenging in egocentric driving videos where the scenes are extremely dynamic. This … |
YU YAO et. al. | IEEE transactions on pattern analysis and machine … | 2022-02-14 |
| 481 | From Unsupervised to Few-shot Graph Anomaly Detection: A Multi-scale Contrastive Learning Approach Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this limitation, we propose a novel framework, graph ANomaly dEtection framework with Multi-scale cONtrastive lEarning (ANEMONE in short). |
YU ZHENG et. al. | arxiv-cs.LG | 2022-02-11 |
| 482 | Meta-learning with GANs for Anomaly Detection, with Deployment in High-speed Rail Inspection System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a meta-learning framework for anomaly detection to deal with these issues. |
Haoyang Cao; Xin Guo; Guan Wang; | arxiv-cs.LG | 2022-02-11 |
| 483 | Anomaly Detection-inspired Few-shot Medical Image Segmentation Through Self-supervision with Supervoxels Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Abstract: Recent work has shown that label-efficient few-shot learning through self-supervision can achieve promising medical image segmentation results. However, few-shot segmentation … |
Stine Hansen; Srishti Gautam; Robert Jenssen; Michael Kampffmeyer; | Medical image analysis | 2022-02-11 |
| 484 | Faster and Better: How Anomaly Detection Can Accelerate and Improve Reporting of Head Computed Tomography Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Most artificial intelligence (AI) systems are restricted to solving a pre-defined task, thus limiting their generalizability to unselected datasets. Anomaly detection relieves … |
TOM FINCK et. al. | Diagnostics (Basel, Switzerland) | 2022-02-10 |
| 485 | Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a data-driven anomaly detection framework using a manufacturing dataset collected from a factory assembly line. |
Kyeong-Joong Jeong; Jin-Duk Park; Kyusoon Hwang; Seong-Lyun Kim; Won-Yong Shin; | arxiv-cs.AI | 2022-02-10 |
| 486 | ARIBA: Towards Accurate and Robust Identification of Backdoor Attacks in Federated Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel method ARIBA to accurately and robustly identify backdoor attacks in federated learning. |
Yuxi Mi; Jihong Guan; Shuigeng Zhou; | arxiv-cs.AI | 2022-02-09 |
| 487 | Log-based Anomaly Detection with Deep Learning: How Far Are We? Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: To achieve a profound understanding of how far we are from solving the problem of log-based anomaly detection, in this paper, we conduct an in-depth analysis of five state-of-the-art deep learning-based models for detecting system anomalies on four public log datasets. |
Van-Hoang Le; Hongyu Zhang; | arxiv-cs.SE | 2022-02-09 |
| 488 | GenAD: General Representations of Multivariate Time Seriesfor Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a General representation of multivariate time series for Anomaly Detection(GenAD). |
XIAOLEI HUA et. al. | arxiv-cs.NI | 2022-02-08 |
| 489 | Detecting Anomalies Within Time Series Using Local Neural Transformations Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We develop a new method to detect anomalies within time series, which is essential in many application domains, reaching from self-driving cars, finance, and marketing to medical diagnosis and epidemiology. |
TIM SCHNEIDER et. al. | arxiv-cs.LG | 2022-02-08 |
| 490 | A Causal Inference Look at Unsupervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Unsupervised video anomaly detection, a task that requires no labeled normal/abnormal training data in any form, is challenging yet of great importance to both industrial … |
Xiangru Lin; Yuyang Chen; Guanbin Li; Yizhou Yu; | aaai | 2022-02-07 |
| 491 | Self-Training Multi-Sequence Learning with Transformer for Weakly Supervised Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the inference stage, we propose to use the video-level anomaly probability to suppress the fluctuation of snippet-level anomaly scores. |
Shuo Li; Fang Liu; Licheng Jiao; | aaai | 2022-02-07 |
| 492 | Region-Based CNN for Anomaly Detection in PV Power Plants Using Aerial Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Today, solar energy is taking an increasing share of the total energy mix. Unfortunately, many operational photovoltaic plants suffer from a plenitude of defects resulting in … |
Michiel Vlaminck; Rugen Heidbuchel; Wilfried Philips; Hiep Luong; | Sensors (Basel, Switzerland) | 2022-02-07 |
| 493 | Towards A Rigorous Evaluation of Time-Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we theoretically and experimentally reveal that the PA protocol has a great possibility of overestimating the detection performance; even a random anomaly score can easily turn into a state-of-the-art TAD method. |
Siwon Kim; Kukjin Choi; Hyun-Soo Choi; Byunghan Lee; Sungroh Yoon; | aaai | 2022-02-07 |
| 494 | Contrastive Predictive Coding for Anomaly Detection in Multi-variate Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Time-series Representational Learning through Contrastive Predictive Coding (TRL-CPC) towards anomaly detection in MVTS data. |
Theivendiram Pranavan; Terence Sim; Arulmurugan Ambikapathi; Savitha Ramasamy; | arxiv-cs.LG | 2022-02-07 |
| 495 | Transferring The Contamination Factor Between Anomaly Detection Domains By Shape Similarity Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Then, estimating the contamination factor for each dataset separately by labeling data would be extremely time-consuming. Therefore, this paper introduces a method for transferring the known contamination factor from one dataset (the source domain) to a related dataset where it is unknown (the target domain). |
Lorenzo Perini; Vincent Vercruyssen; Jesse Davis; | aaai | 2022-02-07 |
| 496 | Robust Anomaly Detection for Time-series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Time-series anomaly detection plays a vital role in monitoring complex operation conditions. However, the detection accuracy of existing approaches is heavily influenced by … |
MIN HU et. al. | arxiv-cs.LG | 2022-02-06 |
| 497 | Margin-aware Intraclass Novelty Identification for Medical Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Existing anomaly detection methods focus on detecting interclass variations while medical image novelty identification is more challenging in the presence of intraclass … |
Xiaoyuan Guo; Judy W Gichoya; Saptarshi Purkayastha; Imon Banerjee; | Journal of medical imaging (Bellingham, Wash.) | 2022-02-03 |
| 498 | Training A Bidirectional GAN-based One-Class Classifier for Network Intrusion Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In our proposed method, we construct the trained encoder-discriminator as a one-class classifier based on Bidirectional GAN (Bi-GAN) for detecting anomalous traffic from normal traffic other than calculating expensive and complex anomaly scores or thresholds. |
Wen Xu; Julian Jang-Jaccard; Tong Liu; Fariza Sabrina; | arxiv-cs.LG | 2022-02-02 |
| 499 | Weighted Random Cut Forest Algorithm for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new RCF algorithm, so-called the weighted RCF (WRCF) algorithm. |
Sijin Yeom; Jae-Hun Jung; | arxiv-cs.LG | 2022-02-01 |
| 500 | Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, in this paper, we compare the performance of different unsupervised deep and machine learning based anomaly detection algorithms, for real-time detection of anomalies on the Audio Video Transport Protocol (AVTP), an application layer protocol implemented in the recent Automotive Ethernet based in-vehicle network. |
Natasha Alkhatib; Maria Mushtaq; Hadi Ghauch; Jean-Luc Danger; | arxiv-cs.LG | 2022-01-31 |
| 501 | An Improved X-means and Isolation Forest Based Methodology for Network Traffic Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in network traffic is becoming a challenging task due to the complexity of large-scale networks and the proliferation of various social network applications. In … |
YIFAN FENG et. al. | PloS one | 2022-01-31 |
| 502 | Time-Series Anomaly Detection with Implicit Neural Representation Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In our paper, we propose a novel method called Implicit Neural Representation-based Anomaly Detection (INRAD). |
Kyeong-Joong Jeong; Yong-Min Shin; | arxiv-cs.LG | 2022-01-28 |
| 503 | An Improved Density Peaks Clustering Algorithm Based on Grid Screening and Mutual Neighborhood Degree for Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the rapid development of network technologies and the increasing amount of network abnormal traffic, network anomaly detection presents challenges. Existing supervised … |
Liangchen Chen; Shu Gao; Baoxu Liu; | Scientific reports | 2022-01-26 |
| 504 | Quantum Anomaly Detection of Audio Samples with A Spin Processor in Diamond Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we experimentally demonstrate a quantum anomaly detection of audio samples with a three-qubit quantum processor consisting of solid-state spins in diamond. |
ZIHUA CHAI et. al. | arxiv-quant-ph | 2022-01-25 |
| 505 | Little Help Makes A Big Difference: Leveraging Active Learning to Improve Unsupervised Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge and improve the overall performance of unsupervised anomaly detection algorithms, we propose to use active learning to introduce and benefit from the feedback of operators, who can verify the alarms (both false and true ones) and label the corresponding KPIs with reasonable effort. |
Hamza Bodor; Thai V. Hoang; Zonghua Zhang; | arxiv-cs.LG | 2022-01-25 |
| 506 | A Hitchhiker’s Guide to Anomaly Detection with Astronomaly Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Here, we present an overview and friendly user guide to the Astronomaly framework for active anomaly detection in astronomical data. |
Michelle Lochner; Bruce A. Bassett; | arxiv-astro-ph.IM | 2022-01-25 |
| 507 | Community-based Anomaly Detection Using Spectral Graph Filtering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a community-based anomaly detection algorithm using a spectral graph-based filter that includes the network community structure into the Laplacian matrix adopted as the basis for the Fourier transform. |
Rodrigo Francisquini; Ana Carolina Lorena; Mariá C. V. Nascimento; | arxiv-cs.SI | 2022-01-24 |
| 508 | Computing Expectation Values of Adaptive Fourier Density Matrices for Quantum Anomaly Detection in NISQ Devices Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: This article presents a novel classical-quantum anomaly detection model based on the expected values of density matrices and a new data embedding called adaptive Fourier features. |
Diego H. Useche; Oscar A. Bustos-Brinez; Joseph A. Gallego; Fabio A. González; | arxiv-quant-ph | 2022-01-24 |
| 509 | An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an unsupervised Attention-based Convolutional Long Short-Term Memory (ConvLSTM) Autoencoder with Dynamic Thresholding (ACLAE-DT) framework for anomaly detection and diagnosis in multivariate time series. |
Tareq Tayeh; Sulaiman Aburakhia; Ryan Myers; Abdallah Shami; | arxiv-cs.LG | 2022-01-22 |
| 510 | Effective Anomaly Detection in Smart Home By Integrating Event Time Intervals Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To fill this gap, in this paper, we propose a novel anomaly detection method that takes the inter-event intervals into consideration. |
Chenxu Jiang; Chenglong Fu; Zhenyu Zhao; Xiaojiang Du; Yuede Ji; | arxiv-cs.CR | 2022-01-19 |
| 511 | TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this paper, we propose TranAD, a deep transformer network based anomaly detection and diagnosis model which uses attention-based sequence encoders to swiftly perform inference with the knowledge of the broader temporal trends in the data. |
Shreshth Tuli; Giuliano Casale; Nicholas R. Jennings; | arxiv-cs.LG | 2022-01-18 |
| 512 | Online Time Series Anomaly Detection with State Space Gaussian Processes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose r-ssGPFA, an unsupervised online anomaly detection model for uni- and multivariate time series building on the efficient state space formulation of Gaussian processes. |
CHRISTIAN BOCK et. al. | arxiv-cs.LG | 2022-01-18 |
| 513 | Antimodes and Graphical Anomaly Exploration Via Depth Quantile Functions Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Abstract: Depth quantile functions (DQF) encode geometric information about a point cloud via functions of a single variable, whereas each observation in a data set can be associated with a … |
Gabriel Chandler; Wolfgang Polonik; | arxiv-stat.ME | 2022-01-17 |
| 514 | Concise Logarithmic Loss Function for Robust Training of Anomaly Detection Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study covers a variety of comparisons from mathematical comparisons, visualization in the differential domain for backpropagation, loss convergence in the training process, and anomaly detection performance. |
YeongHyeon Park; | arxiv-cs.LG | 2022-01-14 |
| 515 | Functional Anomaly Detection: A Benchmark Study Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: It is the purpose of this paper to investigate the performance of recent techniques for anomaly detection in the functional setup on real datasets. |
GUILLAUME STAERMAN et. al. | arxiv-stat.ML | 2022-01-13 |
| 516 | Forecast-based Multi-aspect Framework for Multivariate Time-series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method that tailors to such distinction. |
LAN WANG et. al. | arxiv-cs.LG | 2022-01-13 |
| 517 | A Simple Method for Unsupervised Anomaly Detection: An Application to Web Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: We propose a simple anomaly detection method that is applicable to unlabeled time series data and is sufficiently tractable, even for non-technical entities, by using the density … |
Keisuke Yoshihara; Kei Takahashi; | PloS one | 2022-01-11 |
| 518 | Unsupervised Deep Anomaly Detection for Medical Images Using An Improved Adversarial Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection has been applied in the various disease of medical practice, such as breast cancer, retinal, lung lesion, and skin disease. However, in real-world anomaly … |
Haibo Zhang; Wenping Guo; Shiqing Zhang; Hongsheng Lu; Xiaoming Zhao; | Journal of digital imaging | 2022-01-10 |
| 519 | Adaptive Performance Anomaly Detection for Online Service Systems Via Pattern Sketching Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: Moreover, they are unable to effectively accommodate the ever-changing services in an online fashion. To address these limitations, in this paper, we propose ADSketch, an interpretable and adaptive performance anomaly detection approach based on pattern sketching. |
ZHUANGBIN CHEN et. al. | arxiv-cs.SE | 2022-01-09 |
| 520 | AnomMAN: Detect Anomaly on Multi-view Attributed Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Graph Convolution based framework, AnomMAN, to detect \textbf{Anom}aly on \textbf{M}ulti-view \textbf{A}ttributed \textbf{N}etworks. |
Ling-Hao Chen; He Li; Wenhao Yang; | arxiv-cs.SI | 2022-01-08 |
| 521 | Applications of Signature Methods to Market Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a signatures based machine learning algorithm to detect rare or unexpected items in a given data set of time series type. |
Erdinc Akyildirim; Matteo Gambara; Josef Teichmann; Syang Zhou; | arxiv-q-fin.CP | 2022-01-07 |
| 522 | Detecting Anomaly in Chemical Sensors Via L1-Kernels Based Principal Component Analysis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a new multiplication-free kernel, which is related to the l1-norm for the anomaly detection task. |
Hongyi Pan; Diaa Badawi; Ishaan Bassi; Sule Ozev; Ahmet Enis Cetin; | arxiv-eess.SP | 2022-01-07 |
| 523 | Distributed Online Anomaly Detection for Virtualized Network Slicing Environment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The alternating direction method of multipliers is adopted to achieve the solution for the distributed online PN anomaly detection. |
Weili Wang; Chengchao Liang; Qianbin Chen; Lun Tang; Halim Yanikomeroglu; | arxiv-cs.NI | 2022-01-05 |
| 524 | Using Machine Learning for Anomaly Detection on A System-on-Chip Under Gamma Radiation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper focuses on a novel and different approach: using machine learning algorithms on consumer electronic level Field Programmable Gate Arrays (FPGAs) to tackle TID effects and monitor them to replace before they stop working. |
EDUARDO WEBER WACHTER et. al. | arxiv-cs.LG | 2022-01-05 |
| 525 | Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection suffers from unbalanced data since anomalies are quite rare. Synthetically generated anomalies are a solution to such ill or not fully defined data. However, … |
Adin Ramirez Rivera; Adil Khan; Imad Eddine Ibrahim Bekkouch; Taimoor Shakeel Sheikh; | IEEE transactions on neural networks and learning systems | 2022-01-05 |
| 526 | Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel approach called Adaptive Memory Network with Self-supervised Learning (AMSL) to address these challenges and enhance the generalization ability in unsupervised anomaly detection. |
Yuxin Zhang; Jindong Wang; Yiqiang Chen; Han Yu; Tao Qin; | arxiv-cs.LG | 2022-01-02 |
| 527 | Magnetic Anomaly Detection of Adjacent Parallel Pipelines Using Deep Learning Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
TAO SUN et. al. | Computers & Geosciences | 2022-01-01 |
| 528 | Big Data Analytics With Machine Learning and Deep Learning Methods for Detection of Anomalies in Network Traffic Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Information is vital for any organization to communicate through any network. The growth of internet utilization and the web users increased the cyber threats. Cyber-attacks in … |
Valliammal Narayan; Shanmugapriya D.; | Research Anthology on Big Data Analytics, Architectures, … | 2022-01-01 |
| 529 | An Energy Efficient Health Monitoring Approach with Wireless Body Area Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Wireless Body Area Networks (WBANs) comprise a network of sensors subcutaneously implanted or placed near the body surface and facilitate continuous monitoring of health … |
Seemandhar Jain; Prarthi Jain; Prabhat K. Upadhyay; Jules M. Moualeu; Abhishek Srivastava; | ArXiv | 2022-01-01 |
| 530 | An Integration Method Using Distributed Optical Fiber Sensor and Auto-Encoder Based Deep Learning for Detecting Sulfurized Rust Self-heating of Crude Oil Tanks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Sulfurized rust is the production of corrosion in crude oil tanks. It will be oxidized and self-heating when contacting with air, and the rise of temperature can cause severe … |
Zhi-Chao Zhu; Chu Chengwei; Hai-Tao Bian; Juncheng Jiang; | Journal of Loss Prevention in The Process Industries | 2022-01-01 |
| 531 | GCN-based Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Graph data structures are now widely used and detecting graph anomalies is a challenging task. Traditional anomaly detection methods can achieve good results in the case of … |
Xu Zhang; XueBin Sun; | 2022-01-01 | |
| 532 | Deep Semisupervised Learning-Based Network Anomaly Detection in Heterogeneous Information Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
NAZARII LUTSIV et. al. | Computers, Materials & Continua | 2022-01-01 |
| 533 | A Cascade Reconstruction Model with Generalization Ability Evaluation for Anomaly Detection in Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection plays an important role in surveillance video since it maintains public safety efficiently with low cost. In current works, anomaly detection methods based on … |
Yuanhong Zhong; Xia Chen; Jinyang Jiang; Fan Ren; | Pattern Recognition | 2022-01-01 |
| 534 | A Study of An Engine Anomaly Detection Model IForest-ADOA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In the environment of the Industrial Internet, automatic and effective anomaly detection methods are of great importance to ensure the safety and stability of engines. However, in … |
Liu Liu; Min Xiao; | Journal of Physics: Conference Series | 2022-01-01 |
| 535 | Abnormal Detection Model of Energy Consumption Data in Beneficiation and Metallurgy Enterprises Based on Transfer Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The energy consumption data of beneficiation and metallurgy enterprises has the characteristics of multi-dimensional and timing. An energy consumption data anomaly detection model … |
ZHUCHAO YU et. al. | Journal of Physics: Conference Series | 2022-01-01 |
| 536 | AICrit: A Unified Framework for Real-time Anomaly Detection in Water Treatment Plants Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Gauthama Raman M.R.; Aditya P. Mathur; | Journal of Information Security and Applications | 2022-01-01 |
| 537 | Deep-learning-based Anomaly Detection for Lace Defect Inspection Employing Videos in Production Line Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Bingyu Lu; Ding Xu; Biqing Huang; | Advanced Engineering Informatics | 2022-01-01 |
| 538 | A Hybrid Deep Learning-Based Unsupervised Anomaly Detection in High Dimensional Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Amgad Muneer; Shakirah Mohd Taib; Suliman Mohamed Fati; Abdullateef O. Balogun; Izzatdin Abdul Aziz; | Computers, Materials & Continua | 2022-01-01 |
| 539 | Design of Ionospheric TEC Gradient Anomaly Detection Platform Based on GNSS Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Ionospheric anomalies can seriously threaten important flight phases such as approach and landing, so accurate real-time monitoring is necessary. In this paper, an ionospheric … |
Mingyuan Liu; Tieqiao Hu; | Journal of Physics: Conference Series | 2022-01-01 |
| 540 | NETWORK ANOMALIES DETECTION APPROACH BASED ON WEIGHTED VOTING Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: To avoid information systems malfunction, their integrity disruption, availability violation as well as data confidentiality, it is necessary to detect anomalies in information … |
International Journal of Information Security and Privacy | 2022-01-01 | |
| 541 | AutoLog: Anomaly Detection By Deep Autoencoding of System Logs Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Marta Catillo; Antonio Pecchia; Umberto Villano; | Expert Syst. Appl. | 2022-01-01 |
| 542 | Keeping Our Rivers Clean: Information-theoretic Online Anomaly Detection for Streaming Business Process Events Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Event log anomaly detection aims at identifying anomalous information in the logs generated by the execution of business processes. While several techniques for detecting … |
Jonghyeon Ko; Marco Comuzzi; | Information Systems | 2022-01-01 |
| 543 | Anomaly Detection Under Multiplicative Noise Model Uncertainty Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: State estimators are crucial components of anomaly detectors that are used to monitor cyber-physical systems. Many frequently-used state estimators are susceptible to model risk … |
Venkatraman Renganathan; Benjamin J. Gravell; Justin Ruths; Tyler H. Summers; | IEEE Control Systems Letters | 2022-01-01 |
| 544 | Arrhythmia Classification of LSTM Autoencoder Based on Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
PENGFEI LIU et. al. | Biomed. Signal Process. Control. | 2022-01-01 |
| 545 | Anomaly Detection and Anticipation in High Performance Computing Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In their quest toward Exascale, High Performance Computing (HPC) systems are rapidly becoming larger and more complex, together with the issues concerning their maintenance. … |
Andrea Borghesi; Martin Molan; Michela Milano; Andrea Bartolini; | IEEE Transactions on Parallel and Distributed Systems | 2022-01-01 |
| 546 | Cognitive Analytics Platform with AI Solutions for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
VAIA ROUSOPOULOU et. al. | Computers in Industry | 2022-01-01 |
| 547 | Sensor Data Based Anomaly Detection in Autonomous Vehicles Using Modified Convolutional Neural Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Sivaramakrishnan Rajendar; Vishnu Kumar Kaliappan; | Intelligent Automation & Soft Computing | 2022-01-01 |
| 548 | LogUAD: Log Unsupervised Anomaly Detection Based on Word2Vec Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
JIN WANG et. al. | Computer Systems Science and Engineering | 2022-01-01 |
| 549 | Exploiting The Sparse Characteristics in Probabilistic Feature Space for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract. Nowadays, the low-rank representation (LRR) and deep learning-based methods have received much attention in anomaly detection for hyperspectral images (HSIs). However, … |
Shaoqi Yu; Xiaorun Li; Shuhan Chen; Liaoying Zhao; | Journal of Applied Remote Sensing | 2022-01-01 |
| 550 | Anomaly Detection Using System Logs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is a very important step in building a secure and trustworthy system. Manually it is daunting to analyze and detect failures and anomalies. In this paper, we … |
International Journal of Information Security and Privacy | 2022-01-01 | |
| 551 | A2Log: Attentive Augmented Log Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are … |
THORSTEN WITTKOPP et. al. | ArXiv | 2022-01-01 |
| 552 | Improved Anomaly Detection in Surveillance Videos with Multiple Probabilistic Models Inference Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Zhen Xu; Xiaoqian Zeng; Genlin Ji; Bo Sheng; | Intelligent Automation & Soft Computing | 2022-01-01 |
| 553 | Research on Anomaly Detection of Train Communication Network Based on Long and Short-term Memory Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Aiming at the intrusion detection algorithm based on traditional machine learning, which can not effectively deal with the problems of large quantity, strong timing and high … |
Jianing Guo; | Journal of Physics: Conference Series | 2022-01-01 |
| 554 | Higher-Order Moment-Based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The identification of anomalies is a critical component of operating complex, large-scale and geographically distributed cyber-physical systems. While designing anomaly detectors, … |
Venkatraman Renganathan; Navid Hashemi; Justin Ruths; Tyler H. Summers; | IEEE Control Systems Letters | 2022-01-01 |
| 555 | Rule-Based Anomaly Detection Model with Stateful Correlation Enhancing Mobile Network Security Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Rafia Afzal; Raja Kumar Murugesan; | Intelligent Automation & Soft Computing | 2022-01-01 |
| 556 | Anomaly Detection Method Near Arbitrary Boundary Field for Surface Inspection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Surface inspection of products has become an essential factor in improving appearance quality. Surface inspection is performed using the brightness deviation from the reference … |
Hanjin Cho; Siwoo Lee; Byoungho Lee; | 2022-01-01 | |
| 557 | Torque Anomaly Detection of Nuclear Power Electric Valve Actuator Based on DAE-WDSVVD Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The abnormal detection of nuclear power electric valve actuator components can effectively improve its operation safety and reliability. With the rise of artificial intelligence … |
Junjie Peng; Xin Chen; Mingqiang Li; Yanhui Zhang; | Journal of Physics: Conference Series | 2022-01-01 |
| 558 | Anomaly Detection and Analysis Based on Deep Autoencoder for The Storage Tank Liquid Level of Oil Depot Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In the industrial control system of oil depot, the change of storage tank liquid level is closely related to the transportation process and site management of oil depot. It is of … |
LONG CHENG et. al. | Journal of Physics: Conference Series | 2022-01-01 |
| 559 | A Deep Learning Approach to Anomaly Sequence Detection for High-Resolution Monitoring of Power Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: A deep learning approach is proposed to detect data and system anomalies using high-resolution continuous point-on-wave (CPOW) or phasor measurements. Both the anomaly and … |
Kursat Rasim Mestav; Xinyi Wang; Lang Tong; | IEEE Transactions on Power Systems | 2022-01-01 |
| 560 | Adaptive Particle Filter with Abnormal Detection for Wearable Indoor Pedestrian Navigation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Currently, indoor location-based services (ILBSs) have increasing requirements in people’s daily life. In the meanwhile, the wearable devices are becoming more popular. In this … |
YING CHEN et. al. | Journal of Physics: Conference Series | 2022-01-01 |
| 561 | Video Anomaly Detection with Spatio-temporal Dissociation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in videos remains a challenging task due to the ambiguous definition of anomaly and the complexity of visual scenes from real video data. Different from the … |
YUNPENG CHANG et. al. | Pattern Recognition | 2022-01-01 |
| 562 | Anomaly Detection Based on A Granular Markov Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Since time series are characterized by a substantial volume of data, high levels of noise and the correlation between data in the time series attributes, it becomes challenging to … |
Yanjun Zhou; Huorong Ren; Zhiwu Li; Witold Pedrycz; | Expert Syst. Appl. | 2022-01-01 |
| 563 | Anomaly Detection in Long-term Tunnel Deformation Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Kristof Maes; Wim Salens; Gerrit Feremans; Koen Segher; Stijn François; | Engineering Structures | 2022-01-01 |
| 564 | Power System Anomaly Detection Using Innovation Reduction Properties of Iterated Extended Kalman Filter Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
ZHAOYANG JIN et. al. | International Journal of Electrical Power & Energy Systems | 2022-01-01 |
| 565 | Research and Design of Optimal Solution for Network Traffic Anomaly Based on Multi-objective Decision Algorithm Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: To help maintainers recover from network outages caused by network traffic anomalies, the paper proposes an optimal solution for network traffic anomaly based on multi-objective … |
YIYING YAN et. al. | Journal of Physics: Conference Series | 2022-01-01 |
| 566 | TransLog: A Unified Transformer-based Framework for Log Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose a unified Transformer-based framework for log anomaly detection (\ourmethod{}), which is comprised of the pretraining and adapter-based tuning stage. |
HONGCHENG GUO et. al. | arxiv-cs.LG | 2021-12-31 |
| 567 | Subtractive Aggregation for Attributed Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap, in this paper, we argue that, by using appropriate models, it is sufficient to simply consider neighbor nodes as the background to detect anomalies. |
Shuang Zhou; Qiaoyu Tan; Zhiming Xu; Xiao Huang; Fu-lai Chung; | cikm | 2021-12-30 |
| 568 | Log Sequence Anomaly Detection Method Based on Contrastive Adversarial Training and Dual Feature Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The log messages generated in the system reflect the state of the system at all times. The realization of autonomous detection of abnormalities in log messages can help operators … |
Qiaozheng Wang; Xiuguo Zhang; Xuejie Wang; Zhiying Cao; | Entropy (Basel, Switzerland) | 2021-12-30 |
| 569 | ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Towards this end, we introduce a novel graph anomaly detection framework, namely ANEMONE, to simultaneously identify the anomalies in multiple graph scales. |
MING JIN et. al. | cikm | 2021-12-30 |
| 570 | Unsupervised Cross-system Log Anomaly Detection Via Domain Adaptation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge, we propose a transferable log anomaly detection (LogTAD) framework that leverages the adversarial domain adaptation technique to make log data from different systems have a similar distribution so that the detection model is able to detect anomalies from multiple systems. |
Xiao Han; Shuhan Yuan; | cikm | 2021-12-30 |
| 571 | Detecting Anomalies in Retinal Diseases Using Generative, Discriminative, and Self-supervised Deep Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detectors could be pursued for retinal diagnoses based on artificial intelligence systems that may not have access to training examples for all retinal diseases in all … |
Philippe Burlina; William Paul; T Y Alvin Liu; Neil M Bressler; | JAMA ophthalmology | 2021-12-30 |
| 572 | Machine Learning-Based Anomaly Detection Techniques in Ophthalmology Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Randy Y Lu; Yelena Bagdasarova; Aaron Y Lee; | JAMA ophthalmology | 2021-12-30 |
| 573 | Action Sequence Augmentation for Early Graph-based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: In this work, we propose Eland, a novel framework that uses action sequence augmentation for early anomaly detection. |
TONG ZHAO et. al. | cikm | 2021-12-30 |
| 574 | Anomaly Mining: Past, Present and Future Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly mining finds high-stakes applications in various real-world domains such as cybersecurity, finance, environmental monitoring, to name a few. Therefore, it has been studied … |
Leman Akoglu; | cikm | 2021-12-30 |
| 575 | Towards Anomaly-resistant Graph Neural Networks Via Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to keep the effectiveness of GNNs on anomaly-contaminated graphs, in this paper, we propose a new framework named RARE-GNN (Reinforced Anomaly-REsistant Graph Neural Networks) which can detect anomalies from the input graph and learn anomaly-resistant GNNs simultaneously. |
Kaize Ding; Xuan Shan; Huan Liu; | cikm | 2021-12-30 |
| 576 | Anomaly Detection in Cyber-Physical Systems: Reconstruction of A Prediction Error Feature Space Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our work proposes a novel anomaly detection framework based on error space reconstruction, where genetic algorithms are used to perform hyperparameter optimization of machine learning methods. |
Nuno Oliveira; Norberto Sousa; Jorge Oliveira; Isabel Praça; | arxiv-cs.CR | 2021-12-29 |
| 577 | Monte Carlo EM for Deep Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Related Code Details Highlight: We present a simple yet effective technique for augmenting existing time series models so that they explicitly account for anomalies in the training data. |
François-Xavier Aubet; Daniel Zügner; Jan Gasthaus; | arxiv-cs.LG | 2021-12-29 |
| 578 | Anomaly Detection Using Capsule Networks for High-dimensional Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This study used a capsule network for the anomaly detection task. |
Inderjeet Singh; Nandyala Hemachandra; | arxiv-cs.LG | 2021-12-27 |
| 579 | Dense Anomaly Detection By Robust Learning on Synthetic Negative Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We extend this approach with synthetic negative patches which simultaneously achieve high inlier likelihood and uniform discriminative prediction. |
Matej Grcić; Petra Bevandić; Zoran Kalafatić; Siniša Šegvić; | arxiv-cs.CV | 2021-12-23 |
| 580 | Network Anomaly Detection in Cars: A Case for Time-Sensitive Stream Filtering and Policing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show how Per-Stream Filtering and Policing of IEEE Time-Sensitive Networking (TSN) can be used as a core technology for identifying misbehaving traffic flows in cars, and thereby serve as network anomaly detectors. |
Philipp Meyer; Timo Häckel; Sandra Reider; Franz Korf; Thomas C. Schmidt; | arxiv-cs.NI | 2021-12-21 |
| 581 | UTRAD: Anomaly Detection and Localization with U-Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is an active research field in industrial defect detection and medical disease detection. However, previous anomaly detection works suffer from unstable … |
Liyang Chen; Zhiyuan You; Nian Zhang; Juntong Xi; Xinyi Le; | Neural networks : the official journal of the International …</ |