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. Based in New York, Paper Digest is dedicated to producing high-quality text analysis results that people can acturally use on a daily basis. Since 2018, we have been serving users across the world with a number of exclusive services on ranking, search, tracking and automatic literature review.
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TABLE 1: Paper Digest: Recent Papers on Anomaly Detection
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | 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 |
| 2 | Local Evaluation of Time Series Anomaly Detection Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we first highlight the limitations of the classical precision/recall, as well as the main issues of the recent event-based metrics — for instance, we show that an adversary algorithm can reach high precision and recall on almost any dataset under weak assumption. 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; | arxiv-cs.LG | 2022-06-27 |
| 3 | 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 |
| 4 | 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 |
| 5 | 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 |
| 6 | 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 |
| 7 | Masked Transformer for Image Anomaly Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We thus propose a new model based on the Vision Transformer architecture with patch masking: the input image is split in several patches, and each patch is reconstructed only from the surrounding data, thus ignoring the potentially anomalous information contained in the patch itself. |
Axel De Nardin; Pankaj Mishra; Gian Luca Foresti; Claudio Piciarelli; | International journal of neural systems | 2022-06-21 |
| 8 | R2-AD2: Detecting Anomalies By Analysing The Raw Gradient Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 9 | Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we proposed a Convolutional Recurrent AutoEncoder (CR-AE), which combines an attention-based Convolutional Long-Short-Term Memory (ConvLSTM) network and a Convolutional AutoEncoder. |
Bokun Wang; Caiqian Yang; | Sensors (Basel, Switzerland) | 2022-06-20 |
| 10 | ADBench: Anomaly Detection Benchmark Literature Review Related Patents Related Grants Related Orgs Related Experts 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 55 benchmark datasets, named ADBench. |
Songqiao Han; Xiyang Hu; Hailiang Huang; Mingqi Jiang; Yue Zhao; | arxiv-cs.LG | 2022-06-19 |
| 11 | 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 |
| 12 | 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 Highlight: To solve the problem, A prediction-then-detection anomaly detection method was proposed, and quantitative assessment of network anomalies was developed. |
Sheng Xue; Hualiang Chen; Xiaoliang Zheng; | International journal of machine learning and cybernetics | 2022-06-17 |
| 13 | 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 |
| 14 | 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 |
| 15 | Deep Isolation Forest for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a novel extension of iForest, deep isolation forest. |
Hongzuo Xu; Guansong Pang; Yijie Wang; Yongjun Wang; | arxiv-cs.LG | 2022-06-14 |
| 16 | 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 |
| 17 | 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 |
| 18 | Adaptive Model Pooling for Online Deep Anomaly Detection from A Complex Evolving Data Stream Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.LG | 2022-06-09 |
| 19 | CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 20 | Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 21 | A Unified Model for Multi-class Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present UniAD that accomplishes anomaly detection for multiple classes with a unified framework. |
ZHIYUAN YOU et. al. | arxiv-cs.CV | 2022-06-08 |
| 22 | 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 |
| 23 | Catching Both Gray and Black Swans: Open-Set Supervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 24 | 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 |
| 25 | Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 26 | UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 27 | Anomaly Detection Via Reverse Distillation From One-Class Embedding Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 28 | Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 29 | 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; | arxiv-cs.LG | 2022-06-06 |
| 30 | 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 |
| 31 | 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 |
| 32 | 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 |
| 33 | Anomaly Detection in Surveillance Videos Using Transformer Based Attention Model Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 34 | 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 |
| 35 | Memory-Augmented Generative Adversarial Networks for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a memory-augmented deep learning model for semisupervised anomaly detection (AD). |
Ziyi Yang; Teng Zhang; Iman Soltani Bozchalooi; Eric Darve; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 36 | Comparison of Anomaly Detectors: Context Matters Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Methods perform differently in different contexts, i.e., under a different combination of experimental conditions together with computational time. This explains the variability of the previous results and highlights the importance of careful specification of the context in the publication of a new method. |
Vit Skvara; Jan Franca; Matej Zorek; Tomas Pevny; Vaclav Smidl; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 37 | 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 |
| 38 | 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 |
| 39 | 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 |
| 40 | Deep Graph Learning for Anomalous Citation Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Within the GLAD framework, we propose an algorithm called Citation PUrpose (CPU) to discover the purpose of citation based on citation context. |
Jiaying Liu; Feng Xia; Xu Feng; Jing Ren; Huan Liu; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 41 | 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 |
| 42 | 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 |
| 43 | 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 |
| 44 | Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new deep generative model, Latent Enhanced regression/classification Deep Generative Model (LEDGM), for the anomaly detection problem with multidimensional data. |
Qin Xie; Peng Zhang; Boseon Yu; Jaesik Choi; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 45 | 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 |
| 46 | Automated Anomaly Detection Via Curiosity-Guided Search and Self-Imitation Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap, in this article, we propose AutoAD, an automated anomaly detection framework, which aims to search for an optimal neural network model within a predefined search space. |
YUENING LI et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 47 | Memorizing Structure-Texture Correspondence for Image Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we utilize two kinds of complementary structures (i.e., the semantic structure with human-labeled category information and the low-level structure with abundant details), which are extracted by two structure extractors. |
KANG ZHOU et. al. | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 48 | 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 |
| 49 | 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 |
| 50 | An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article presents a systematic and comprehensive evaluation of unsupervised and semisupervised deep-learning-based methods for anomaly detection and diagnosis on multivariate time series data from cyberphysical systems. |
Astha Garg; Wenyu Zhang; Jules Samaran; Ramasamy Savitha; Chuan-Sheng Foo; | IEEE transactions on neural networks and learning systems | 2022-06-01 |
| 51 | 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 |
| 52 | MAD-EN: Microarchitectural Attack Detection Through System-wide Energy Consumption Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 53 | Correlation-Based Anomaly Detection Method for Multi-sensor System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: That is, the method can effectively detect anomalies of multidimensional time series. |
HAN LI et. al. | Computational intelligence and neuroscience | 2022-05-31 |
| 54 | 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 |
| 55 | Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 56 | Rethinking Graph Neural Networks for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We demonstrate the effectiveness of BWGNN on four large-scale anomaly detection datasets. |
Jianheng Tang; Jiajin Li; Ziqi Gao; Jia Li; | arxiv-cs.LG | 2022-05-30 |
| 57 | 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 |
| 58 | 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 |
| 59 | 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 |
| 60 | 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 |
| 61 | Raising The Bar in Graph-level Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.LG | 2022-05-27 |
| 62 | 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 |
| 63 | 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 |
| 64 | 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 |
| 65 | 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; | arxiv-cs.LG | 2022-05-23 |
| 66 | MOSPAT: AutoML Based Model Selection and Parameter Tuning for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 67 | 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 |
| 68 | Detecting Cyberattacks on Electrical Storage Systems Through Neural Network Based Anomaly Detection Algorithm Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper analyzes the vulnerabilities of BESS and proposes an anomaly detection algorithm that, by observing the physical behavior of the system, aims to promptly detect dangerous working conditions by exploiting the capabilities of a particular neural network architecture called the autoencoder. |
GIOVANNI BATTISTA GAGGERO et. al. | Sensors (Basel, Switzerland) | 2022-05-23 |
| 69 | 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; | arxiv-cs.LG | 2022-05-22 |
| 70 | An Innovative Huffman Forest-Based Method to Detected Railroad Station Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Three types of anomalies (local clustered, axis paralleled, and surrounded by normal instances) caused by the specialty of railroad operations bring the existing methods non-trivial challenges in detecting them accurately and efficiently. To tackle this limitation of existing methods, this paper proposes a novel anomaly detection method named Huffman Anomaly Detection Forest (HuffForest) to detect station anomalies, which leverages Huffman encoding to measure abnormalities in certain railroad scenarios with high accuracy. |
Yuan Wang; Xiaopeng Li; | Sensors (Basel, Switzerland) | 2022-05-22 |
| 71 | 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 |
| 72 | Self-supervised Anomaly Detection for New Physics Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 73 | 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 Highlight: This paper presents a systematic review of acoustic approaches in mechanical failure detection in terms of recent implementations and structural extensions. |
Ahmad Qurthobi; Rytis Maskeliūnas; Robertas Damaševičius; | Sensors (Basel, Switzerland) | 2022-05-20 |
| 74 | Time Series Anomaly Detection Via Reinforcement Learning-Based Model Selection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, due to the complex nature of real-world data, different anomalies within a time series usually have diverse profiles supporting different anomaly assumptions, making it difficult to find a single anomaly detector that can consistently beat all other models. In this work, to harness the benefits of different base models, we assume that a pool of anomaly detection models is accessible and propose to utilize reinforcement learning to dynamically select a candidate model from these base models. |
Jiuqi Elise Zhang; Di Wu; Benoit Boulet; | arxiv-cs.LG | 2022-05-19 |
| 75 | 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 |
| 76 | Anomaly Detection Using Prediction Error with Spatio-Temporal Convolutional LSTM Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 77 | 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 |
| 78 | 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 |
| 79 | 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 |
| 80 | 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 |
| 81 | Anomaly Detection and Community Detection in Networks Literature Review Related Patents Related Grants Related Orgs Related Experts 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 which incorporates domain knowledge, i.e., community membership, as a fundamental model for regular behavior, and thus flag potential anomalies deviating from this pattern. |
Hadiseh Safdari; Caterina De Bacco; | arxiv-cs.SI | 2022-05-12 |
| 82 | 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 |
| 83 | 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 |
| 84 | 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 |
| 85 | Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest Radiographs Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 86 | Randomized Geometric Tools for Anomaly Detection in Stock Markets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose novel randomized geometric tools to detect low-volatility anomalies in stock markets; a principal problem in financial economics. |
Cyril Bachelard; Apostolos Chalkis; Vissarion Fisikopoulos; Elias Tsigaridas; | arxiv-cs.CG | 2022-05-08 |
| 87 | 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. | |
| 88 | 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 |
| 89 | 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 |
| 90 | 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 |
| 91 | 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 |
| 92 | 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 |
| 93 | 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 |
| 94 | 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 |
| 95 | 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 |
| 96 | 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 |
| 97 | 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 |
| 98 | MemStream: Memory-Based Streaming Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 99 | 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 |
| 100 | A Novel Traffic Accident Detection Method with Comprehensive Traffic Flow Features Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose three new traffic flow features, namely the road congestion, the traffic intensity, and the traffic state instability, for more comprehensive traffic status representation and anomaly detection. |
Liping Zhu; Bingyao Wang; Yihan Yan; Shuang Guo; Gangyi Tian; | Signal, image and video processing | 2022-04-28 |
| 101 | Anomaly Detection By Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.LG | 2022-04-28 |
| 102 | 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 |
| 103 | IRC-safe Graph Autoencoder for An 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 |
| 104 | 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 |
| 105 | A Survey on Unsupervised 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 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 |
| 106 | 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 |
| 107 | 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 |
| 108 | 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 |
| 109 | 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 |
| 110 | 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 |
| 111 | A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We extensively reviewed twelve of the most popular unsupervised anomaly detection methods. |
MAXIME ALVAREZ et. al. | arxiv-cs.LG | 2022-04-20 |
| 112 | Sintel: A Machine Learning Framework to Extract Insights from Signals Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 113 | 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 |
| 114 | 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 |
| 115 | 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 |
| 116 | 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 |
| 117 | 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 |
| 118 | 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 |
| 119 | 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 |
| 120 | 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 |
| 121 | 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; | ||
| 122 | 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 |
| 123 | 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 |
| 124 | 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 |
| 125 | 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 |
| 126 | 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 |
| 127 | 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 |
| 128 | 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 |
| 129 | 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 |
| 130 | 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 |
| 131 | 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 |
| 132 | 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 |
| 133 | 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 |
| 134 | Proactive Anomaly Detection for Robot Navigation with Multi-Sensor Fusion Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 135 | 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 |
| 136 | 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 |
| 137 | A Survey of Single-Scene Video Anomaly Detection IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article summarizes research trends on the topic of anomaly detection in video feeds of a single scene. |
Bharathkumar Ramachandra; Michael J Jones; Ranga Raju Vatsavai; | IEEE transactions on pattern analysis and machine … | 2022-04-01 |
| 138 | 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 |
| 139 | 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 |
| 140 | Contextual Information Based Anomaly Detection for A Multi-Scene UAV Aerial Videos Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 141 | 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 |
| 142 | AnoDFDNet: A Deep Feature Difference Network for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 143 | 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 |
| 144 | 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 |
| 145 | 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 |
| 146 | SIFT and SURF Based Feature Extraction for The Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 147 | 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 |
| 148 | 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 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 |
| 149 | Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 150 | An End-to-end Computer Vision Methodology for Quantitative Metallography Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 151 | 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 |
| 152 | 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 |
| 153 | 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 |
| 154 | Anomaly Detection in Emails Using Machine Learning and Header Information Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 155 | Nonnegative-Constrained Joint Collaborative Representation with Union Dictionary for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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 |
| 156 | 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 |
| 157 | The Analysis of Online Event Streams: Predicting The Next Activity for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 158 | 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 |
| 159 | Practical Data Monitoring in The Internet-services Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a framework for reliable large-scale anomaly detection. |
Nikhil Galagali; | arxiv-cs.LG | 2022-03-15 |
| 160 | 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 |
| 161 | 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 |
| 162 | An Empirical Investigation of 3D Anomaly Detection and Segmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The objective of this paper is to further understand the benefit and role of 3D as opposed to color in image anomaly detection. |
Eliahu Horwitz; Yedid Hoshen; | arxiv-cs.CV | 2022-03-10 |
| 163 | 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 |
| 164 | TiSAT: Time Series Anomaly Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 165 | 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 |
| 166 | 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 |
| 167 | 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 |
| 168 | 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 |
| 169 | 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 |
| 170 | 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 |
| 171 | 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 |
| 172 | Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 173 | 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 |
| 174 | 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 |
| 175 | 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 |
| 176 | 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. |
Layne Bradshaw; Spencer Chang; Bryan Ostdiek; | arxiv-hep-ph | 2022-03-02 |
| 177 | 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 |
| 178 | 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 |
| 179 | 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 |
| 180 | Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 181 | 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 |
| 182 | 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 |
| 183 | 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 |
| 184 | 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 |
| 185 | Do Autoencoders Need A Bottleneck for Anomaly Detection? Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 186 | 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 |
| 187 | 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 |
| 188 | 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 |
| 189 | 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 |
| 190 | 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 |
| 191 | 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 |
| 192 | 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 |
| 193 | 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 |
| 194 | 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 |
| 195 | Composite Anomaly Detection Via Hierarchical Dynamic Search Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a sequential search strategy using two variations of the Generalized Local Likelihood Ratio statistic. |
Benjamin Wolff; Tomer Gafni; Guy Revach; Nir Shlezinger; Kobi Cohen; | arxiv-cs.IT | 2022-02-21 |
| 196 | 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 |
| 197 | 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 |
| 198 | Anomalib: A Deep Learning Library for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 199 | Latent Outlier Exposure for Anomaly Detection with Contaminated Data Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.LG | 2022-02-16 |
| 200 | Deep Generative Model with Hierarchical Latent Factors for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 201 | 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 |
| 202 | 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 |
| 203 | Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 204 | 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 |
| 205 | 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 |
| 206 | A Survey of Visual Sensory Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 207 | 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 |
| 208 | Adaptive Graph Convolutional Networks for Weakly Supervised Anomaly Detection in Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For weakly supervised anomaly detection, most existing work is limited to the problem of inadequate video representation due to the inability of modeling long-term contextual information. To solve this, we propose a novel weakly supervised adaptive graph convolutional network (WAGCN) to model the complex contextual relationship among video segments. |
Congqi Cao; Xin Zhang; Shizhou Zhang; Peng Wang; Yanning Zhang; | arxiv-cs.CV | 2022-02-14 |
| 209 | Anomaly Detection-inspired Few-shot Medical Image Segmentation Through Self-supervision with Supervoxels Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 210 | 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 |
| 211 | 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 |
| 212 | UMAP Based Anomaly Detection for Minimal Residual Disease Quantification Within Acute Myeloid Leukemia Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Leukemia is the most frequent malignancy in children and adolescents, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) as the most common subtypes. Minimal … |
LISA WEIJLER et. al. | Cancers | 2022-02-11 |
| 213 | 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 |
| 214 | 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 |
| 215 | 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 |
| 216 | Log-based Anomaly Detection with Deep Learning: How Far Are We? Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 217 | 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 |
| 218 | Detecting Anomalies Within Time Series Using Local Neural Transformations Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 219 | 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 |
| 220 | 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 |
| 221 | 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 |
| 222 | 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 |
| 223 | 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 |
| 224 | 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 |
| 225 | 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 |
| 226 | 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 |
| 227 | Time-Series Anomaly Detection with Implicit Neural Representation Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 228 | 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 |
| 229 | 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 |
| 230 | 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 |
| 231 | A Hitchhiker’s Guide to Anomaly Detection with Astronomaly Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 232 | 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 |
| 233 | 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 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 |
| 234 | 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 |
| 235 | 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 |
| 236 | TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 237 | 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 |
| 238 | Antimodes and Graphical Anomaly Exploration Via Depth Quantile Functions Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 239 | 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 |
| 240 | 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 |
| 241 | 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 |
| 242 | 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 |
| 243 | 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 |
| 244 | Adaptive Performance Anomaly Detection for Online Service Systems Via Pattern Sketching Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 245 | 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 |
| 246 | 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 |
| 247 | 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 |
| 248 | 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 |
| 249 | 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 |
| 250 | 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 |
| 251 | 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 |
| 252 | 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 |
| 253 | 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 |
| 254 | 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: 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 … |
Zhi-Chao Zhu; Chu Chengwei; Hai-Tao Bian; Juncheng Jiang; | Journal of Loss Prevention in The Process Industries | 2022-01-01 |
| 255 | 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 |
| 256 | 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 |
| 257 | 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 |
| 258 | 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: 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 … |
Yuanhong Zhong; Xia Chen; Jinyang Jiang; Fan Ren; | Pattern Recognition | 2022-01-01 |
| 259 | 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 |
| 260 | 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 | |
| 261 | 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 |
| 262 | 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 | |
| 263 | 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 |
| 264 | 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 |
| 265 | 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 |
| 266 | 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 | |
| 267 | 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 |
| 268 | 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 |
| 269 | 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 |
| 270 | 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 |
| 271 | 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 |
| 272 | 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: 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 |
| 273 | 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 |
| 274 | 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 |
| 275 | 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 | |
| 276 | 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 |
| 277 | 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 |
| 278 | 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 |
| 279 | 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 |
| 280 | 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 |
| 281 | 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 |
| 282 | 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 |
| 283 | 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 |
| 284 | 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 |
| 285 | 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 |
| 286 | 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 |
| 287 | Video Anomaly Detection with Spatio-temporal Dissociation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: 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 … |
YUNPENG CHANG et. al. | Pattern Recognition | 2022-01-01 |
| 288 | Anomaly Detection Based on A Granular Markov Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: 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 … |
Yanjun Zhou; Huorong Ren; Zhiwu Li; Witold Pedrycz; | Expert Syst. Appl. | 2022-01-01 |
| 289 | 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 |
| 290 | 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 |
| 291 | 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 |
| 292 | 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 |
| 293 | 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 |
| 294 | 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 |
| 295 | 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 |
| 296 | 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 |
| 297 | 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 |
| 298 | 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 |
| 299 | Action Sequence Augmentation for Early Graph-based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 300 | 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 |
| 301 | 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 |
| 302 | Monte Carlo EM for Deep Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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 |
| 303 | 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 |
| 304 | 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 |
| 305 | 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 … | 2021-12-21 |
| 306 | 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 |
| 307 | Anomaly Clustering: Grouping Images Into Coherent Clusters of Anomaly Types Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a simple yet effective clustering framework using a patch-based pretrained deep embeddings and off-the-shelf clustering methods. |
Kihyuk Sohn; Jinsung Yoon; Chun-Liang Li; Chen-Yu Lee; Tomas Pfister; | arxiv-cs.CV | 2021-12-21 |
| 308 | Projected Sliced Wasserstein Autoencoder-based Hyperspectral Images Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose the Projected Sliced Wasserstein (PSW) autoencoder-based anomaly detection method. |
Yurong Chen; Hui Zhang; Yaonan Wang; Q. M. Jonathan Wu; Yimin Yang; | arxiv-cs.CV | 2021-12-20 |
| 309 | Deep Graph-level Anomaly Detection By Glocal Knowledge Distillation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge we introduce a novel deep anomaly detection approach for GAD that learns rich global and local normal pattern information by joint random distillation of graph and node representations. |
Rongrong Ma; Guansong Pang; Ling Chen; Anton van den Hengel; | arxiv-cs.CV | 2021-12-19 |
| 310 | Efficient Anomaly Detection from Medical Signals and Images with Convolutional Neural Networks for Internet of Medical Things (IoMT) Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Deep learning is one of the most promising machine learning techniques that revolutionalized the artificial intelligence field. The known traditional and convolutional neural … |
ALI A KHALIL et. al. | International journal for numerical methods in biomedical … | 2021-12-18 |
| 311 | The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the first comprehensive 3D dataset for the task of unsupervised anomaly detection and localization. |
Paul Bergmann; Xin Jin; David Sattlegger; Carsten Steger; | arxiv-cs.CV | 2021-12-16 |
| 312 | Anomaly Detection in Particle Accelerators Using Autoencoders Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we explore the use of autoencoder reconstruction analysis for the prediction of magnet faults in the Advanced Photon Source (APS) storage ring at Argonne National Laboratory. |
Jonathan P. Edelen; Nathan M. Cook; | arxiv-physics.acc-ph | 2021-12-14 |
| 313 | Approaches Toward Physical and General Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the Physical Anomalous Trajectory or Motion (PHANTOM) dataset, which contains six different video classes. |
Laura Kart; Niv Cohen; | arxiv-cs.CV | 2021-12-14 |
| 314 | Noise Reduction and Driving Event Extraction Method for Performance Improvement on Driving Noise-based Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple driving event extraction method and noise reduction method for improving computational efficiency and anomaly detection performance. |
YeongHyeon Park; JoonSung Lee; Myung Jin Kim; Wonseok Park; | arxiv-cs.SD | 2021-12-14 |
| 315 | Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper develops a method to explain the anomaly predictions of the state-of-the-art Isolation Forest anomaly detection algorithm. |
Nirmal Sobha Kartha; Clément Gautrais; Vincent Vercruyssen; | arxiv-cs.LG | 2021-12-13 |
| 316 | A Comprehensive Study of Anomaly Detection Schemes in IoT Networks Using Machine Learning Algorithms Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The Internet of Things (IoT) consists of a massive number of smart devices capable of data collection, storage, processing, and communication. The adoption of the IoT has brought … |
Abebe Diro; Naveen Chilamkurti; Van-Doan Nguyen; Will Heyne; | Sensors (Basel, Switzerland) | 2021-12-13 |
| 317 | DeepFIB: Self-Imputation for Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this problem, we propose a novel self-supervised learning technique for AD in time series, namely \emph{DeepFIB}. |
Minhao Liu; Zhijian Xu; Qiang Xu; | arxiv-cs.LG | 2021-12-12 |
| 318 | Anomaly Crossing: A New Method for Video Anomaly Detection As Cross-domain Few-shot Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, to address this issue, we propose a new learning paradigm by making full use of both normal and abnormal videos for video anomaly detection. |
Guangyu Sun; Zhang Liu; Lianggong Wen; Jing Shi; Chenliang Xu; | arxiv-cs.CV | 2021-12-12 |
| 319 | Improvement of Human Error Prediction Accuracy in Single-trial Analysis of Electroencephalogram Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The prevention of human error is an important task that has already been researched. Previous studies have shown that EEG signals can predict the occurrence of human errors. … |
D Nishiura; I Nambu; Y Maruyama; Y Wada; | Annual International Conference of the IEEE Engineering in … | 2021-12-11 |
| 320 | Inception-GAN for Semi-supervised Detection of Pneumonia in Chest X-rays Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Recent advances in Deep Learning have led to the development of supervised models to detect anomalies in medical images such as pneumonia in chest X-rays. Automatic detection of … |
Saman Motamed; Farzad Khalvati; | Annual International Conference of the IEEE Engineering in … | 2021-12-11 |
| 321 | Anomaly Detection in Blockchain Networks: A Comprehensive Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we provide an in-depth survey regarding integration of anomaly detection models in blockchain technology. |
Muneeb Ul Hassan; Mubashir Husain Rehmani; Jinjun Chen; | arxiv-cs.CR | 2021-12-11 |
| 322 | Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Lung nodules are commonly missed in chest radiographs. We propose and evaluate P-AnoGAN, an unsupervised anomaly detection approach for lung nodules in radiographs. P-AnoGAN … |
Nitish Bhatt; David Ramon Prados; Nedim Hodzic; Christos Karanassios; H R Tizhoosh; | Annual International Conference of the IEEE Engineering in … | 2021-12-11 |
| 323 | Deep Learning-based User Authentication with Surface EMG Images of Hand Gestures Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: User authentication is an important security mechanism to prevent unauthorized accesses to systems or devices. In this paper, we propose a new user authentication method based on … |
Qingqing Li; Zhirui Luo; Jun Zheng; | Annual International Conference of the IEEE Engineering in … | 2021-12-11 |
| 324 | Multimedia Datasets for Anomaly Detection: A Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a comprehensive survey on a variety of video, audio, as well as audio-visual datasets based on the application of anomaly detection. |
Pratibha Kumari; Anterpreet Kaur Bedi; Mukesh Saini; | arxiv-cs.CV | 2021-12-10 |
| 325 | Fast and Scalable Neuroevolution Deep Learning Architecture Search for Multivariate Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, a modified neuroevolution technique is presented which incorporates multi-level optimisation. |
M. Pietroń; D. Żurek; K. Faber; | arxiv-cs.NE | 2021-12-10 |
| 326 | Anomaly Detection in High-energy Physics Using A Quantum Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The lack of evidence for new interactions and particles at the Large Hadron Collider has motivated the high-energy physics community to explore model-agnostic data-analysis approaches to search for new physics. |
Vishal S. Ngairangbam; Michael Spannowsky; Michihisa Takeuchi; | arxiv-hep-ph | 2021-12-09 |
| 327 | Ymir: A Supervised Ensemble Framework for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We proposed a multivariate time series anomaly detection frame-work Ymir, which leverages ensemble learning and supervisedlearning technology to efficiently learn and adapt to anomaliesin real-world system applications. |
Zhanxiang Zhao; | arxiv-cs.LG | 2021-12-09 |
| 328 | Adaptive Packet Transmission in Response to Anomaly Detection in Software Defined Smart Meter Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we examine a basic smart meter network topology in mininet and address the issue of congestion over a commodity network, proposing an adaptive algorithm to cope with varying grid data delivery latencies. |
Mihnea Maris; Thomas Halpin; Dubem Ezeh; Karen Miu; Jaudelice de Oliveira; | arxiv-cs.NI | 2021-12-08 |
| 329 | Abnormal Detection in Big Data Video with An Improved Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the rapid growth of video surveillance data, there is an increasing demand for big data automatic anomaly detection of large-scale video data. The detection methods using … |
Yihan Bian; Xinchen Tang; | Computational intelligence and neuroscience | 2021-12-08 |
| 330 | Statistics-Based Outlier Detection and Correction Method for Amazon Customer Reviews Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: People nowadays use the internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These … |
Ishani Chatterjee; Mengchu Zhou; Abdullah Abusorrah; Khaled Sedraoui; Ahmed Alabdulwahab; | Entropy (Basel, Switzerland) | 2021-12-07 |
| 331 | The LHC Olympics 2020 A Community Challenge for Anomaly Detection in High Energy Physics IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. … |
GREGOR KASIECZKA et. al. | Reports on progress in physics. Physical Society (Great … | 2021-12-07 |
| 332 | Regularity Learning Via Explicit Distribution Modeling for Skeletal Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, a novel Motion Embedder (ME) is proposed to provide a pose motion representation from the probability perspective. |
SHOUBIN YU et. al. | arxiv-cs.CV | 2021-12-07 |
| 333 | Online False Discovery Rate Control for Anomaly Detection in Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article proposes novel rules for false discovery rate control (FDRC) geared towards online anomaly detection in time series. |
Quentin Rebjock; Barış Kurt; Tim Januschowski; Laurent Callot; | arxiv-stat.ML | 2021-12-06 |
| 334 | Constrained Adaptive Projection with Pretrained Features for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.CV | 2021-12-05 |
| 335 | Self-Supervision-Augmented Deep Autoencoder for Unsupervised Visual Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Deep autoencoder (AE) has demonstrated promising performances in visual anomaly detection (VAD). Learning normal patterns on normal data, deep AE is expected to yield larger … |
CHAO HUANG et. al. | IEEE transactions on cybernetics | 2021-12-01 |
| 336 | Semi-Supervised Surface Anomaly Detection of Composite Wind Turbine Blades From Drone Imagery Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we address automating the otherwise time-consuming task of both blade detection and extraction, together with fault detection within UAV-captured turbine blade inspection imagery. |
Jack. W. Barker; Neelanjan Bhowmik; Toby. P. Breckon; | arxiv-cs.CV | 2021-12-01 |
| 337 | Lightweight Anomaly Detection Scheme Using Incremental Principal Component Analysis and Support Vector Machine Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Wireless Sensors Networks have been the focus of significant attention from research and development due to their applications of collecting data from various fields such as smart … |
NURFAZRINA M ZAMRY et. al. | Sensors (Basel, Switzerland) | 2021-11-30 |
| 338 | Anomaly Detection for Medical Images Using Self-Supervised and Translation-Consistent Features Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: As the labeled anomalous medical images are usually difficult to acquire, especially for rare diseases, the deep learning based methods, which heavily rely on the large amount of … |
HE ZHAO et. al. | IEEE transactions on medical imaging | 2021-11-30 |
| 339 | TiWS-iForest: Isolation Forest in Weakly Supervised and Tiny ML Scenarios Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Beside showing iForest training limitations, we propose here TiWS-iForest, an approach that, by leveraging weak supervision is able to reduce Isolation Forest complexity and to enhance detection performances. |
Tommaso Barbariol; Gian Antonio Susto; | arxiv-cs.LG | 2021-11-30 |
| 340 | Anomaly Rule Detection in Sequence Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a new anomaly detection framework called DUOS that enables Discovery of Utility-aware Outlier Sequential rules from a set of sequences. |
Wensheng Gan; Lili Chen; Shicheng Wan; Jiahui Chen; Chien-Ming Chen; | arxiv-cs.DB | 2021-11-29 |
| 341 | Anomaly-Aware Semantic Segmentation By Leveraging Synthetic-Unknown Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Observing this, we propose a novel Synthetic-Unknown Data Generation, intending to tackle the anomaly-aware semantic segmentation task. |
GUAN-RONG LU et. al. | arxiv-cs.CV | 2021-11-29 |
| 342 | Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new method for testing antenna arrays that records the radiating electromagnetic (EM) field using an absorbing material and evaluating the resulting thermal image series through an AI using a conditional encoder-decoder model. |
Hans Hao-Hsun Hsu; Jiawen Xu; Ravi Sama; Matthias Kovatsch; | arxiv-cs.LG | 2021-11-27 |
| 343 | Distributed Anomaly Detection in Edge Streams Using Frequency Based Sketch Datastructures Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose MDistrib and its variants which provides (a) faster detection of anomalous events via distributed processing with GPU support compared to other approaches, (b) better false positive guarantees than state of the art methods considering fixed space and (c) with collision aware based anomaly scoring for better accuracy results than state-of-the-art approaches. |
Prateek Chanda; Malay Bhattacharya; | arxiv-cs.DC | 2021-11-27 |
| 344 | Deep Learning-based Anomaly-onset Aware Remaining Useful Life Estimation of Bearings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Remaining Useful Life (RUL) estimation of rotating machinery based on their degradation data is vital for machine supervisors. Deep learning models are effective and popular … |
Pooja Vinayak Kamat; Rekha Sugandhi; Satish Kumar; | PeerJ. Computer science | 2021-11-26 |
| 345 | A Taxonomy of Anomalies in Log Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a taxonomy for different kinds of log data anomalies and introduce a method for analyzing such anomalies in labeled datasets. |
Thorsten Wittkopp; Philipp Wiesner; Dominik Scheinert; Odej Kao; | arxiv-cs.DB | 2021-11-26 |
| 346 | In-painting Radiography Images for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose space-aware memory queues for in-painting and detecting anomalies from radiography images (abbreviated as SQUID). |
TIANGE XIANG et. al. | arxiv-cs.CV | 2021-11-26 |
| 347 | Efficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to make the re-colorization task more object-oriented than background-oriented, we propose to include the contextual color information of the image border via an attention mechanism. |
Loic Jezequel; Ngoc-Son Vu; Jean Beaudet; Aymeric Histace; | arxiv-cs.CV | 2021-11-24 |
| 348 | SLA$^2$P: Self-supervised Anomaly Detection with Adversarial Perturbation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel and powerful framework, dubbed as SLA$^2$P, for unsupervised anomaly detection. |
YIZHOU WANG et. al. | arxiv-cs.LG | 2021-11-24 |
| 349 | An Explainable and Efficient Deep Learning Framework for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Deep learning-based video anomaly detection methods have drawn significant attention in the past few years due to their superior performance. However, almost all the leading … |
Chongke Wu; Sicong Shao; Cihan Tunc; Pratik Satam; Salim Hariri; | Cluster computing | 2021-11-23 |
| 350 | Event-based Anomaly Detection for New Physics Searches at The LHC Using Machine Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper discusses model-agnostic searches for new physics at the Large Hadron Collider (LHC) using anomaly-detection techniques for the identification of event signatures that deviate from the Standard Model (SM). |
S. V. Chekanov; W. Hopkins; | arxiv-hep-ph | 2021-11-23 |
| 351 | Unsupervised Anomaly Detection of MEMS in Low Illumination Based on Polarimetric Support Vector Data Description Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Low illuminated images make it challenging to conduct anomaly detection on material surface. Adding polarimetric information helps expand pixel range and recover background … |
Yaokang Huang; Mei Sang; Lun Xing; Haofeng Hu; Tiegen Liu; | Optics express | 2021-11-23 |
| 352 | Efficient Non-Compression Auto-Encoder for Driving Noise-based Road Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose a convolutional auto-encoder-based anomaly detection model for taking both less computational resources and achieving higher anomaly detection performance. |
YeongHyeon Park; JongHee Jung; | arxiv-cs.CV | 2021-11-21 |
| 353 | Using A Nested Anomaly Detection Machine Learning Algorithm to Study The Neutral Triple Gauge Couplings at An \texorpdfstring{$e^+e^-$}{e+e-} Collider Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this difficulty, we propose a nested anomaly detection algorithm, which appears to be useful in the study of neutral triple gauge couplings at the CEPC, the ILC and the FCC-ee. |
Ji-Chong Yang; Yu-Chen Guo; Li-Hua Cai; | arxiv-hep-ph | 2021-11-20 |
| 354 | Online False Discovery Rate Control for Anomaly Detection in Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article proposes novel rules for false discovery rate control (FDRC) geared towards online anomaly detection in time series. |
Quentin Rebjock; Baris Kurt; Tim Januschowski; Laurent Callot; | nips | 2021-11-20 |
| 355 | Future Frame Prediction Network for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Video Anomaly detection in videos refers to the identification of events that do not conform to expected behavior. However, almost all existing methods cast this problem as the … |
Weixin Luo; Wen Liu; Dongze Lian; Shenghua Gao; | IEEE transactions on pattern analysis and machine … | 2021-11-19 |
| 356 | UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main aspect of novelty of UN-AVOIDS is that it transforms data into a new space, which is introduced in this paper as neighborhood cumulative density function (NCDF), in which both visualization and detection are carried out. |
Waleed A. Yousef; Issa Traore; William Briguglio; | arxiv-cs.LG | 2021-11-18 |
| 357 | LAnoBERT : System Log Anomaly Detection Based on BERT Masked Language Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Particularly, a template corresponding to a specific event should be defined in advance for all the log data using which the information within the log key may get lost.In this study, we propose LAnoBERT, a parser free system log anomaly detection method that uses the BERT model, exhibiting excellent natural language processing performance. |
Yukyung Lee; Jina Kim; Pilsung Kang; | arxiv-cs.LG | 2021-11-18 |
| 358 | UniMAP: Model-free Detection of Unclassified Noise Transients in LIGO-Virgo Data Using The Temporal Outlier Factor Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the Unicorn Multi-window Anomaly-detection Pipeline (UniMAP): a model-free algorithm to identify and characterize transient noise leveraging the Temporal Outlier Factor (TOF) via a multi-window data-resampling scheme. |
Julian Ding; Raymond Ng; Jess McIver; | arxiv-gr-qc | 2021-11-17 |
| 359 | Semi-supervised Automatic Seizure Detection Using Personalized Anomaly Detecting Variational Autoencoder with Behind-the-ear EEG Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Epilepsy is one of the most common neurologic diseases worldwide, and 30% of the patients live with uncontrolled seizures. For the safety of patients with epilepsy, an automatic … |
Sungmin You; Baek Hwan Cho; Young-Min Shon; Dae-Won Seo; In Young Kim; | Computer methods and programs in biomedicine | 2021-11-17 |
| 360 | Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Different from related methods, we propose to integrate the reconstruction-based functionality into a novel self-supervised predictive architectural building block. |
NICOLAE-CATALIN RISTEA et. al. | arxiv-cs.CV | 2021-11-17 |
| 361 | Online Self-Evolving Anomaly Detection in Cloud Computing Environments Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a \emph{self-evolving anomaly detection} (SEAD) framework for cloud dependability assurance. |
HAILI WANG et. al. | arxiv-cs.DC | 2021-11-16 |
| 362 | Survey on Security Issues of Routing and Anomaly Detection for Space Information Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Space information networks is network systems that can receive, transmit, and process spatial information lively. It uses satellites, stratosphere airships, Unmanned Aerial … |
Ming Zhuo; Leyuan Liu; Shijie Zhou; Zhiwen Tian; | Scientific reports | 2021-11-15 |
| 363 | FastFlow: Unsupervised Anomaly Detection and Localization Via 2D Normalizing Flows Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose FastFlow implemented with 2D normalizing flows and use it as the probability distribution estimator. |
JIAWEI YU et. al. | arxiv-cs.CV | 2021-11-15 |
| 364 | Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose GLUE (Graph Deviation Network with Local Uncertainty Estimation), building on the recently proposed Graph Deviation Network (GDN). |
Saswati Ray; Sana Lakdawala; Mononito Goswami; Chufan Gao; | arxiv-cs.LG | 2021-11-15 |
| 365 | Weakly Supervised Video Anomaly Detection Based on 3D Convolution and LSTM Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Weakly supervised video anomaly detection is a recent focus of computer vision research thanks to the availability of large-scale weakly supervised video datasets. However, most … |
Zhen Ma; José J M Machado; João Manuel R S Tavares; | Sensors (Basel, Switzerland) | 2021-11-12 |
| 366 | Parallel Anomaly Detection Algorithm for Cybersecurity on The Highspeed Train Control System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: With the rapid development of the high-speed train industry, the high-speed train control system has now been exposed to a complicated network environment full of dangers. This … |
ZHOUKAI WANG et. al. | Mathematical biosciences and engineering : MBE | 2021-11-12 |
| 367 | Variation and Generality in Encoding of Syntactic Anomaly Information in Sentence Embeddings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we aim to fill two primary gaps, focusing on the domain of syntactic anomalies. |
Qinxuan Wu; Allyson Ettinger; | arxiv-cs.CL | 2021-11-12 |
| 368 | Online-compatible Unsupervised Non-resonant Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the first complete strategy for unsupervised detection of non-resonant anomalies that includes both signal sensitivity and a data-driven method for background estimation. |
Vinicius Mikuni; Benjamin Nachman; David Shih; | arxiv-cs.LG | 2021-11-11 |
| 369 | Few-shot Domain-adaptive Anomaly Detection for Cross-site Brain Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Early screening is essential for effective intervention and treatment of individuals with mental disorders. Functional magnetic resonance imaging (fMRI) is a noninvasive tool for … |
Jianpo Su; Hui Shen; Limin Peng; Dewen Hu; | IEEE transactions on pattern analysis and machine … | 2021-11-08 |
| 370 | Data-Driven Anomaly Detection in High-Voltage Transformer Bushings with LSTM Auto-Encoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The reliability and health of bushings in high-voltage (HV) power transformers is essential in the power supply industry, as any unexpected failure can cause power outage leading … |
Imene Mitiche; Tony McGrail; Philip Boreham; Alan Nesbitt; Gordon Morison; | Sensors (Basel, Switzerland) | 2021-11-08 |
| 371 | Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Multivariate time series anomaly detection is a widespread problem in the field of failure prevention. Fast prevention means lower repair costs and losses. The amount of sensors … |
Kamil Faber; Marcin Pietron; Dominik Zurek; | Entropy (Basel, Switzerland) | 2021-11-06 |
| 372 | A Multilayer LSTM Auto-Encoder for Fetal ECG Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The paper introduces a multilayer long short-term memory (LSTM) based auto-encoder network to spot abnormalities in fetal ECG. The LSTM network was used to detect patterns in the … |
Inna Skarga-Bandurova; Tetiana Biloborodova; Illia Skarha-Bandurov; Yehor Boltov; Maryna Derkach; | Studies in health technology and informatics | 2021-11-04 |
| 373 | Anomaly Detection from Mass Unspecific Jet Tagging Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel anomaly search method based on (i) jet tagging to select interesting events, which are less likely to be produced by background processes; (ii) comparison of the untagged and tagged samples to single out features (such as bumps produced by the decay of new particles) in the latter. |
J. A. Aguilar-Saavedra; | arxiv-hep-ph | 2021-11-04 |
| 374 | Graph Regularized Deep Sparse Representation for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection (AD) aims to distinguish the data points that are inconsistent with the overall pattern of the data. Recently, unsupervised anomaly detection methods have … |
Shicheng Li; Shumin Lai; Yan Jiang; Wenle Wang; Yugen Yi; | Computational intelligence and neuroscience | 2021-11-03 |
| 375 | A Critical Study on The Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces the researchers of the field to a new perspective and reviews the recent deep-learning based semi-supervised video anomaly detection approaches, based on a common strategy they use for anomaly detection. |
Mohammad Baradaran; Robert Bergevin; | arxiv-cs.CV | 2021-11-02 |
| 376 | A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, in order to improve the efficiency and accuracy of best so far time series analysis-based ECG anomaly detection methods, a novel method, comprising a modified dynamic time warping (MDTW) and an innovative average non-self match distance (ANSD) measure, is proposed for ECG anomaly detection. |
Hua-Liang Wei; | arxiv-eess.SP | 2021-11-01 |
| 377 | Evaluation of An Anomaly Detector for Routers Using Parameterizable Malware in An IoT Ecosystem Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work explores the evaluation of a machine learning anomaly detector using custom-made parameterizable malware in an Internet of Things (IoT) Ecosystem. |
John Carter; Spiros Mancoridis; | arxiv-cs.CR | 2021-10-29 |
| 378 | Autoencoder-based Anomaly Detection in Smart Farming Ecosystem Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an anomaly detection model for Smart Farming using an unsupervised Autoencoder machine learning model. |
Mary Adkisson; Jeffrey C Kimmel; Maanak Gupta; Mahmoud Abdelsalam; | arxiv-cs.CR | 2021-10-29 |
| 379 | Boosting Anomaly Detection Using Unsupervised Diverse Test-Time Augmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the Test-Time Augmentation for anomaly Detection (TTAD) technique, a TTA-based method aimed at improving anomaly detection performance. |
Seffi Cohen; Niv Goldshlager; Lior Rokach; Bracha Shapira; | arxiv-cs.LG | 2021-10-29 |
| 380 | Generalized Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study anomaly detection for the case when the normal class consists of more than one object category. |
Suresh Singh; Minwei Luo; Yu Li; | arxiv-cs.LG | 2021-10-28 |
| 381 | Anomaly-Injected Deep Support Vector Data Description for Text Outlier Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we target the textual anomaly detection problem and propose a deep anomaly-injected support vector data description (AI-SVDD) framework. |
Zeyu You; Yichu Zhou; Tao Yang; Wei Fan; | arxiv-cs.CL | 2021-10-27 |
| 382 | Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Normality-Calibrated Autoencoder (NCAE), which can boost anomaly detection performance on the contaminated datasets without any prior information or explicit abnormal samples in the training phase. |
Jongmin Yu; Hyeontaek Oh; Minkyung Kim; Junsik Kim; | arxiv-cs.LG | 2021-10-27 |
| 383 | Unsupervised Anomaly Detection in MR Images Using Multicontrast Information Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in magnetic resonance imaging (MRI) is to distinguish the relevant biomarkers of diseases from those of normal tissues. In this paper, an unsupervised algorithm … |
Byungjai Kim; Kinam Kwon; Changheun Oh; Hyunwook Park; | Medical physics | 2021-10-26 |
| 384 | A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This survey aims to provide a cross-domain and comprehensive review of numerous eminent works in respective areas while identifying their commonalities. |
MOHAMMADREZA SALEHI et. al. | arxiv-cs.CV | 2021-10-26 |
| 385 | DeepSense: A Physics-Guided Deep Learning Paradigm for Anomaly Detection in Soil Gas Data at Geologic CO 2 Storage Sites Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Driven by the collection of enormous amounts of streaming data from sensors, and with the emergence of the internet of things, the need for developing robust detection techniques … |
Sahar Bakhshian; Katherine Romanak; | Environmental science & technology | 2021-10-25 |
| 386 | Latent-Insensitive Autoencoders for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we introduce Latent-Insensitive autoencoder (LIS-AE) where unlabeled data from a similar domain is utilized as negative examples to shape the latent layer (bottleneck) of a regular autoencoder such that it is only capable of reconstructing one task. |
Muhammad S. Battikh; Artem A. Lenskiy; | arxiv-cs.LG | 2021-10-25 |
| 387 | Patch Vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Good candidate approaches are patch-based unsupervised pipelines which have both the advantage to increase the number of input data and to capture local and fine anomaly patterns distributed in the image, while potential inconveniences are the loss of global structural information. |
Verónica Muñoz-Ramírez; Nicolas Pinon; Florence Forbes; Carole Lartizen; Michel Dojat; | arxiv-eess.IV | 2021-10-25 |
| 388 | A Semi-supervised Approach to Dark Matter Searches in Direct Detection Data with Machine Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general philosophy more concrete by applying modern machine learning techniques to dark matter direct detection. |
Juan Herrero-Garcia; Riley Patrick; Andre Scaffidi; | arxiv-hep-ph | 2021-10-23 |
| 389 | Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a systematic literature review of the applications of GANs in anomaly detection, covering 128 papers on the subject. |
Mikael Sabuhi; Ming Zhou; Cor-Paul Bezemer; Petr Musilek; | arxiv-cs.LG | 2021-10-22 |
| 390 | Uncertainty Aware Anomaly Detection to Predict Errant Beam Pulses in The SNS Accelerator Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: As such, we describe the applicationof an uncertainty aware Machine Learning method, the Siamese neural network model, to predictupcoming errant beam pulses using the data from a single monitoring device. |
WILLEM BLOKLAND et. al. | arxiv-physics.acc-ph | 2021-10-22 |
| 391 | Integrated Multiscale Appearance Features and Motion Information Prediction Network for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The rise of video-prediction algorithms has largely promoted the development of anomaly detection in video surveillance for smart cities and public security. However, most current … |
Ting Liu; Chengqing Zhang; Liming Wang; | Computational intelligence and neuroscience | 2021-10-20 |
| 392 | Multiresolution Dendritic Cell Algorithm for Network Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection in computer networks is a complex task that requires the distinction of normality and anomaly. Network attack detection in information systems is a constant … |
David Limon-Cantu; Vicente Alarcon-Aquino; | PeerJ. Computer science | 2021-10-19 |
| 393 | Learning Not to Reconstruct Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate this problem, we propose a novel methodology to train AEs with the objective of reconstructing only normal data, regardless of the input (i.e., normal or abnormal). |
Marcella Astrid; Muhammad Zaigham Zaheer; Jae-Yeong Lee; Seung-Ik Lee; | arxiv-cs.CV | 2021-10-19 |
| 394 | Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To mitigate this, we propose a temporal pseudo anomaly synthesizer that generates fake-anomalies using only normal data. |
Marcella Astrid; Muhammad Zaigham Zaheer; Seung-Ik Lee; | arxiv-cs.CV | 2021-10-19 |
| 395 | Improving Variational Autoencoders for New Physics Detection at The LHC with Normalizing Flows Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. |
PRATIK JAWAHAR et. al. | arxiv-hep-ph | 2021-10-16 |
| 396 | Anomaly Detection in Multi-Agent Trajectories for Automated Driving Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose the spatio-temporal graph auto-encoder for learning normal driving behaviours. Due to the lack of multi-agent trajectory datasets for anomaly detection in automated driving, we introduce our dataset using a driving simulator for normal and abnormal manoeuvres. |
Julian Wiederer; Arij Bouazizi; Marco Troina; Ulrich Kressel; Vasileios Belagiannis; | arxiv-cs.RO | 2021-10-15 |
| 397 | Memory-augmented Adversarial Autoencoders for Multivariate Time-series Anomaly Detection with Deep Reconstruction and Prediction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the above issues, we propose MemAAE (\textit{Memory-augmented Adversarial Autoencoders with Deep Reconstruction and Prediction}), a novel unsupervised anomaly detection method for time-series. |
Qinfeng Xiao; Shikuan Shao; Jing Wang; | arxiv-cs.LG | 2021-10-15 |
| 398 | Challenges for Unsupervised Anomaly Detection in Particle Physics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study some challenges associated with variational autoencoders, such as the dependence on hyperparameters and the metric used, in the context of anomalous signal (top and $W$) jets in a QCD background. |
Katherine Fraser; Samuel Homiller; Rashmish K. Mishra; Bryan Ostdiek; Matthew D. Schwartz; | arxiv-cs.LG | 2021-10-13 |
| 399 | Searches for New Physics in Collision Events Using A Statistical Technique for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper discusses a statistical anomaly-detection method for model-independent searches for new physics in collision events produced at the Large Hadron Collider (LHC). |
S. V. Chekanov; | arxiv-hep-ph | 2021-10-12 |
| 400 | Remote Anomaly Detection in Industry 4.0 Using Resource-Constrained Devices Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider the specific problem of remote anomaly detection based on signals that fall into the latter category over wireless channels with resource-constrained sensors. |
Anders E. Kalør; Daniel Michelsanti; Federico Chiariotti; Zheng-Hua Tan; Petar Popovski; | arxiv-cs.IT | 2021-10-12 |
| 401 | Deep Video Anomaly Detection: Opportunities and Challenges Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a comprehensive review of deep learning-based methods to detect the video anomalies from a new perspective. |
Jing Ren; Feng Xia; Yemeng Liu; Ivan Lee; | arxiv-cs.CV | 2021-10-11 |
| 402 | Where’s Swimmy?: Mining Unique Color Features Buried in Galaxies By Deep Anomaly Detection Using Subaru Hyper Suprime-Cam Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the Swimmy (Subaru WIde-field Machine-learning anoMalY) survey program, a deep-learning-based search for unique sources using multicolored ($grizy$) imaging data from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). |
TAKUMI S. TANAKA et. al. | arxiv-astro-ph.GA | 2021-10-11 |
| 403 | Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Towards this end, we propose a novel framework for unsupervised anomaly detection and localization. |
YE ZHENG et. al. | arxiv-cs.CV | 2021-10-09 |
| 404 | DRAEM – A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In addition to reconstructive approach, we cast surface anomaly detection primarily as a discriminative problem and propose a discriminatively trained reconstruction anomaly embedding model (DRAEM). |
Vitjan Zavrtanik; Matej Kristan; Danijel Skocaj; | iccv | 2021-10-08 |
| 405 | Anomaly Detection of Water Level Using Deep Autoencoder Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is one of the crucial tasks in daily infrastructure operations as it can prevent massive damage to devices or resources, which may then lead to catastrophic … |
Isack Thomas Nicholaus; Jun Ryeol Park; Kyuil Jung; Jun Seoung Lee; Dae-Ki Kang; | Sensors (Basel, Switzerland) | 2021-10-08 |
| 406 | A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we consider the setting of few-shot anomaly detection in images, where only a few images are given at training. |
Shelly Sheynin; Sagie Benaim; Lior Wolf; | iccv | 2021-10-08 |
| 407 | Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In light of this, this study proposes a Hankel-structured tensor version of RPCA for anomaly detection in spatiotemporal data. |
Xudong Wang; Luis Miranda-Moreno; Lijun Sun; | arxiv-cs.LG | 2021-10-08 |
| 408 | Learning Unsupervised Metaformer for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper addresses two pivotal issues of reconstruction-based approaches to AD in images, namely, model adaptation and reconstruction gap. |
Jhih-Ciang Wu; Ding-Jie Chen; Chiou-Shann Fuh; Tyng-Luh Liu; | iccv | 2021-10-08 |
| 409 | Road Anomaly Detection By Partial Image Reconstruction With Segmentation Coupling Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel approach to the detection of unknown objects in the context of autonomous driving. |
TOMAS VOJIR et. al. | iccv | 2021-10-08 |
| 410 | Divide-and-Assemble: Learning Block-Wise Memory for Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we interpret the reconstruction of an image as a divide-and-assemble procedure. |
JINLEI HOU et. al. | iccv | 2021-10-08 |
| 411 | Weakly-Supervised Video Anomaly Detection With Robust Temporal Feature Magnitude Learning IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we introduce a novel and theoretically sound method, named Robust Temporal Feature Magnitude learning (RTFM), which trains a feature magnitude learning function to effectively recognise the positive instances, substantially improving the robustness of the MIL approach to the negative instances from abnormal videos. |
YU TIAN et. al. | iccv | 2021-10-08 |
| 412 | AnoSeg: Anomaly Segmentation Network Using Self-Supervised Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a novel anomaly segmentation network (AnoSeg) that can directly generate an accurate anomaly map using self-supervised learning. |
Jouwon Song; Kyeongbo Kong; Ye-In Park; Seong-Gyun Kim; Suk-Ju Kang; | arxiv-eess.IV | 2021-10-07 |
| 413 | Differential Anomaly Detection for Facial Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Due to their convenience and high accuracy, face recognition systems are widely employed in governmental and personal security applications to automatically recognise individuals. … |
MATHIAS IBSEN et. al. | arxiv-cs.CV | 2021-10-07 |
| 414 | Hyperspectral Anomaly Detection Via Super-resolution Reconstruction with An Attention Mechanism Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Hyperspectral anomaly detection aims to classify the anomalous objects in the scene. However, the spatial resolution of the hyperspectral images is relatively low, leading to … |
Dan Chong; Bingliang Hu; Hao Gao; Xiaohui Gao; | Applied optics | 2021-10-06 |
| 415 | Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Technically, we propose the \emph{Anomaly Transformer} with a new \emph{Anomaly-Attention} mechanism to compute the association discrepancy. |
Jiehui Xu; Haixu Wu; Jianmin Wang; Mingsheng Long; | arxiv-cs.LG | 2021-10-06 |
| 416 | A Uniform Framework for Anomaly Detection in Deep Neural Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we consider three classes of anomaly inputs, (1) natural inputs from a different distribution than the DNN is trained for, known as Out-of-Distribution (OOD) samples, (2) crafted inputs generated from ID by attackers, often known as adversarial (AD) samples, and (3) noise (NS) samples generated from meaningless data. |
Fangzhen Zhao; Chenyi Zhang; Naipeng Dong; Zefeng You; Zhenxin Wu; | arxiv-cs.LG | 2021-10-06 |
| 417 | An Efficient Anomaly Detection Approach Using Cube Sampling with Streaming Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend our previous work by proposed an efficient iForest based approach for anomaly detection using cube sampling that is effective on streaming data. |
Seemandhar Jain; Prarthi Jain; Abhishek Srivastava; | arxiv-cs.LG | 2021-10-05 |
| 418 | A Multi-Scale A Contrario Method for Unsupervised Image Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose an a contrario framework to detect anomalies in images applying statistical analysis to feature maps obtained via convolutions. |
Matias Tailanian; Pablo Musé; Álvaro Pardo; | arxiv-cs.CV | 2021-10-05 |
| 419 | LogDP: Combining Dependency and Proximity for Log-based Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we propose a novel semi-supervised log-based anomaly detection approach, LogDP, which utilizes the dependency relationships among log events and proximity among log sequences to detect the anomalies in massive unlabeled log data. |
Yongzheng Xie; Hongyu Zhang; Bo Zhang; Muhammad Ali Babar; Sha Lu; | arxiv-cs.SE | 2021-10-05 |
| 420 | In-Network Processing Acoustic Data for Anomaly Detection in Smart Factory Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider acoustic data-based anomaly detection, which is widely used in factories because sound information reflects richer internal states while videos cannot; besides, the capital investment of an audio system is more economically friendly. |
Huanzhuo Wu; Yunbin Shen; Xun Xiao; Artur Hecker; Frank H. P. Fitzek; | arxiv-cs.NI | 2021-10-04 |
| 421 | Self-Supervised Out-of-Distribution Detection and Localization with Natural Synthetic Anomalies (NSA) Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new self-supervised task, NSA, for training an end-to-end model for anomaly detection and localization using only normal data. |
Hannah M. Schlüter; Jeremy Tan; Benjamin Hou; Bernhard Kainz; | arxiv-cs.CV | 2021-09-30 |
| 422 | Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to develop more advanced deep learning models for ADS. |
Chungjun Lee; Jibum Hong; DongNyeong Heo; Heeyoul Choi; | arxiv-cs.LG | 2021-09-29 |
| 423 | Video Abnormal Event Detection Based on One-Class Neural Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Video abnormal event detection is a challenging problem in pattern recognition field. Existing methods usually design the two steps of video feature extraction and anomaly … |
Xiangli Xia; Yang Gao; | Computational intelligence and neuroscience | 2021-09-28 |
| 424 | Y-GAN: Learning Dual Data Representations for Efficient Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel reconstruction-based model for anomaly detection, called Y-GAN. |
Marija Ivanovska; Vitomir Štruc; | arxiv-cs.CV | 2021-09-28 |
| 425 | An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an implementation of an automated data engineering pipeline for anomaly detection of IoT sensor data is studied and proposed. |
Xinze Li; Baixi Zou; | arxiv-cs.LG | 2021-09-28 |
| 426 | Quantum Algorithms for Anomaly Detection Using Amplitude Estimation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we find that Liang et al.’s algorithm doesn’t actually execute. |
MING-CHAO GUO et. al. | arxiv-quant-ph | 2021-09-28 |
| 427 | Anomaly Detection for High-Dimensional Data Using Large Deviations Principle Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an anomaly detection algorithm that can scale to high-dimensional data using concepts from the theory of large deviations. |
Sreelekha Guggilam; Varun Chandola; Abani Patra; | arxiv-cs.LG | 2021-09-28 |
| 428 | Visual Anomaly Detection for Images: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we provide a comprehensive survey of the classical and deep learning-based approaches for visual anomaly detection in the literature. |
Jie Yang; Ruijie Xu; Zhiquan Qi; Yong Shi; | arxiv-cs.CV | 2021-09-27 |
| 429 | The Value of Human Data Annotation for Machine Learning Based Anomaly Detection in Environmental Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, … |
STEFANIA RUSSO et. al. | Water research | 2021-09-27 |
| 430 | DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose DeepAID, a general framework aiming to (1) interpret DL-based anomaly detection systems in security domains, and (2) improve the practicality of these systems based on the interpretations. |
DONGQI HAN et. al. | arxiv-cs.CR | 2021-09-23 |
| 431 | An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a systematic and comprehensive evaluation of unsupervised and semi-supervised deep-learning based methods for anomaly detection and diagnosis on multivariate time series data from cyberphysical systems. |
Astha Garg; Wenyu Zhang; Jules Samaran; Savitha Ramasamy; Chuan-Sheng Foo; | arxiv-cs.LG | 2021-09-23 |
| 432 | DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the DeTAVIZ interface, which is a web browser based visualization tool for quick exploration and assessment of feasibility of DL based anomaly detection in a given problem. |
Błażej Leporowski; Casper Hansen; Alexandros Iosifidis; | arxiv-cs.LG | 2021-09-21 |
| 433 | A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a simple yet effective anomaly detection framework for deep RL algorithms that simultaneously considers random, adversarial and out-of-distribution~(OOD) state outliers. |
Hongming Zhang; Ke Sun; Bo Xu; Linglong Kong; Martin Müller; | arxiv-cs.LG | 2021-09-20 |
| 434 | Low-Rank and Sparse Decomposition With Mixture of Gaussian for Hyperspectral Anomaly Detection IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Recently, the low-rank and sparse decomposition model (LSDM) has been used for anomaly detection in hyperspectral imagery. The traditional LSDM assumes that the sparse component … |
Lu Li; Wei Li; Qian Du; Ran Tao; | IEEE transactions on cybernetics | 2021-09-15 |
| 435 | Anomaly Detection With Representative Neighbors Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Identifying anomalies from data has attracted increasing attention in recent years due to its broad range of potential applications. Although many efforts have been made for … |
Huawen Liu; Xiaodan Xu; Enhui Li; Shichao Zhang; Xuelong Li; | IEEE transactions on neural networks and learning systems | 2021-09-14 |
| 436 | Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detection IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Recurrent Neural Networks are powerful machine learning frameworks that allow for data to be saved and referenced in a temporal sequence. |
Joseph M. Ackerson; Dave Rushit; Seliya Jim; | arxiv-cs.LG | 2021-09-13 |
| 437 | Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we tackle the problem of Semi-Supervised Anomaly Segmentation (SAS) in Magnetic Resonance Images (MRI) of the brain, which is the task of automatically identifying pathologies in brain images. |
Felix Meissen; Georgios Kaissis; Daniel Rueckert; | arxiv-eess.IV | 2021-09-13 |
| 438 | ConAnomaly: Content-Based Anomaly Detection for System Logs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Enterprise systems typically produce a large number of logs to record runtime states and important events. Log anomaly detection is efficient for business management and system … |
Dan Lv; Nurbol Luktarhan; Yiyong Chen; | Sensors (Basel, Switzerland) | 2021-09-13 |
| 439 | LEA-Net: Layer-wise External Attention Network for Efficient Color Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel model called Layer-wise External Attention Network (LEA-Net) for efficient image anomaly detection. |
Ryoya Katafuchi; Terumasa Tokunaga; | arxiv-cs.CV | 2021-09-12 |
| 440 | Towards A Rigorous Evaluation of Time-series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we theoretically and experimentally reveal that the PA protocol has a great possibility of overestimating the detection performance; that is, 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; | arxiv-cs.LG | 2021-09-11 |
| 441 | A Secondary Immune Response Based on Co-evolutive Populations of Agents for Anomaly Detection and Characterization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: An ABS based anomaly classifier model is presented, incorporating elements of the AIS. |
Pedro Pinacho-Davidson; Matías Lermanda; Ricardo Contreras; María A. Pinninghoff; | arxiv-cs.CR | 2021-09-11 |
| 442 | Enhancing Unsupervised Anomaly Detection with Score-Guided Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To that end, this work proposes a novel scoring network with a score-guided regularization to learn and enlarge the anomaly score disparities between normal and abnormal data. |
ZONGYUAN HUANG et. al. | arxiv-cs.LG | 2021-09-10 |
| 443 | TENET: Temporal CNN with Attention for Anomaly Detection in Automotive Cyber-Physical Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a novel anomaly detection framework called TENET to detect anomalies induced by cyber-attacks on vehicles. |
S. V. Thiruloga; V. K. Kukkala; S. Pasricha; | arxiv-cs.LG | 2021-09-09 |
| 444 | Detecting Attacks on IoT Devices Using Featureless 1D-CNN Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we introduce a Featureless machine learning process to perform anomaly detection. |
Arshiya Khan; Chase Cotton; | arxiv-cs.CR | 2021-09-08 |
| 445 | Intrusion Detection Using Network Traffic Profiling and Machine Learning for IoT Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper explores the potential of using network profiling and machine learning to secure IoT against cyber-attacks. |
Joseph Rose; Matthew Swann; Gueltoum Bendiab; Stavros Shiaeles; Nicholas Kolokotronis; | arxiv-cs.CR | 2021-09-06 |
| 446 | Postulating Exoplanetary Habitability Via A Novel Anomaly Detection Method Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: A profound shift in the study of cosmology came with the discovery of thousands of exoplanets and the possibility of the existence of billions of them in our Galaxy. |
Jyotirmoy Sarkar; Kartik Bhatia; Snehanshu Saha; Margarita Safonova; Santonu Sarkar; | arxiv-astro-ph.EP | 2021-09-06 |
| 447 | Gen2Out: Detecting and Ranking Generalized Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our main contribution is the gen2Out algorithm, that has the following desirable properties: (a) Principled and Sound anomaly scoring that obeys the axioms for detectors, (b) Doubly-general in that it detects, as well as ranks generalized anomaly — both point- and group-anomalies, (c) Scalable, it is fast and scalable, linear on input size. |
Meng-Chieh Lee; Shubhranshu Shekhar; Christos Faloutsos; T. Noah Hutson; Leon Iasemidis; | arxiv-cs.LG | 2021-09-06 |
| 448 | Deep Set Auto Encoders for Anomaly Detection in Particle Physics IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a Deep Set Variational Autoencoder and present results on the Dark Machines Anomaly Score Challenge. |
Bryan Ostdiek; | arxiv-hep-ph | 2021-09-03 |
| 449 | Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Advanced machine-learning (ML) techniques can potentially detect the entire spectrum of pathology through deviations from a learned norm. We investigated the utility of a weakly … |
TOM FINCK et. al. | Clinical neuroradiology | 2021-08-31 |
| 450 | Online Anomaly Detection With Bandwidth Optimized Hierarchical Kernel Density Estimators Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: We propose a novel unsupervised anomaly detection algorithm that can work for sequential data from any complex distribution in a truly online framework with mathematically proven … |
Mine Kerpicci; Huseyin Ozkan; Suleyman Serdar Kozat; | IEEE transactions on neural networks and learning systems | 2021-08-31 |
| 451 | Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an end-to-end model of Deep Dual Support Vector Data description based Autoencoder (Dual-SVDAE) for anomaly detection on attributed networks, which considers both the structure and attribute for attributed networks. |
Fengbin Zhang; Haoyi Fan; Ruidong Wang; Zuoyong Li; Tiancai Liang; | arxiv-cs.LG | 2021-08-31 |
| 452 | Automatic Detection of Basal Cell Carcinoma By Hyperspectral Imaging Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The purpose of this study was to test the ability of hyperspectral imaging (HSI) combined with unsupervised anomaly detectors to automatically differentiate basal cell carcinoma … |
Mihaela Antonina Calin; Sorin Viorel Parasca; | Journal of biophotonics | 2021-08-30 |
| 453 | OneFlow: One-class Flow for Anomaly Detection Based on A Minimal Volume Region Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: We propose OneFlow – a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. Contrary to density-based methods, OneFlow is … |
LUKASZ MAZIARKA et. al. | IEEE transactions on pattern analysis and machine … | 2021-08-30 |
| 454 | High-dimensional Anomaly Detection with Radiative Return in $e^{+}e^{-}$ Collisions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show that machine learning methods that use imperfect or missing training labels can achieve sensitivity to generic new particle production in radiative return events. |
Julia Gonski; Jerry Lai; Benjamin Nachman; Inês Ochoa; | arxiv-hep-ph | 2021-08-30 |
| 455 | Thermal Management in Large Data Centers: Security Threats and Mitigation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on this issue by analysing the potential security threats to these systems and their impact on the overall data center safety and performance. |
Betty Saridou; Gueltoum Bendiab; Stavros N. Shiaeles; Basil K. Papadopoulos; | arxiv-cs.CR | 2021-08-30 |
| 456 | Deep-Compact-Clustering Based Anomaly Detection Applied to Electromechanical Industrial Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The rapid growth in the industrial sector has required the development of more productive and reliable machinery, and therefore, leads to complex systems. In this regard, the … |
Francisco Arellano-Espitia; Miguel Delgado-Prieto; Artvin-Darien Gonzalez-Abreu; Juan Jose Saucedo-Dorantes; Roque Alfredo Osornio-Rios; | Sensors (Basel, Switzerland) | 2021-08-30 |
| 457 | Anomaly Detection of Defect Using Energy of Point Pattern Features Within Random Finite Set Framework Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient approach for industrial defect detection that is modeled based on anomaly detection using point pattern data. |
Ammar Mansoor Kamoona; Amirali Khodadadian Gostar; Alireza Bab-Hadiashar; Reza Hoseinnezhad; | arxiv-cs.CV | 2021-08-27 |
| 458 | Anomaly Detection on IT Operation Series Via Online Matrix Profile Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, the online matrix profile, which requires no training, is proposed to address this issue. |
Shi-Ying Lan; Run-Qing Chen; Wan-Lei Zhao; | arxiv-cs.LG | 2021-08-26 |
| 459 | A Deep CNN Model for Anomaly Detection and Localization in Wireless Capsule Endoscopy Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Wireless capsule endoscopy (WCE) is one of the most efficient methods for the examination of gastrointestinal tracts. Computer-aided intelligent diagnostic tools alleviate the … |
SAMIR JAIN et. al. | Computers in biology and medicine | 2021-08-25 |
| 460 | Image-based Insider Threat Detection Via Geometric Transformation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel insider threat detection method, Image-based Insider Threat Detector via Geometric Transformation (IGT), which converts the unsupervised anomaly detection into supervised image classification task, and therefore the performance can be boosted via computer vision techniques. |
DONGYANG LI et. al. | arxiv-cs.CR | 2021-08-24 |
| 461 | Generative and Contrastive Self-Supervised Learning for Graph Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome these challenges, in this paper, we propose a novel method, Self-Supervised Learning for Graph Anomaly Detection (SL-GAD). |
YU ZHENG et. al. | arxiv-cs.LG | 2021-08-22 |
| 462 | Research on The Fastest Detection Method for Weak Trends Under Noise Interference Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Trend anomaly detection is the practice of comparing and analyzing current and historical data trends to detect real-time abnormalities in online industrial data-streams. It has … |
Guang Li; Jing Liang; Caitong Yue; | Entropy (Basel, Switzerland) | 2021-08-22 |
| 463 | Weakly-supervised Joint Anomaly Detection and Classification Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose a method that jointly handles the anomaly detection and classification in a single framework by adopting a weakly-supervised learning paradigm. |
Snehashis Majhi; Srijan Das; Francois Bremond; Ratnakar Dash; Pankaj Kumar Sa; | arxiv-cs.CV | 2021-08-20 |
| 464 | CloudShield: Real-time Anomaly Detection in The Cloud Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose CloudShield, a practical and generalizable real-time anomaly and attack detection system for cloud computing. |
Zecheng He; Ruby B. Lee; | arxiv-cs.CR | 2021-08-19 |
| 465 | Federated Variational Learning for Anomaly Detection in Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle these issues, we propose an unsupervised time series anomaly detection framework in a federated fashion to continuously monitor the behaviors of interconnected devices within a network and alerts for abnormal incidents so that countermeasures can be taken before undesired consequences occur. |
KAI ZHANG et. al. | arxiv-cs.LG | 2021-08-18 |
| 466 | A Novel Framework for Anomaly Detection for Satellite Momentum Wheel Based on Optimized SVM and Huffman-Multi-Scale Entropy Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The health status of the momentum wheel is vital for a satellite. Recently, research on anomaly detection for satellites has become more and more extensive. Previous research … |
Yuqing Li; Mingjia Lei; Pengpeng Liu; Rixin Wang; Minqiang Xu; | Entropy (Basel, Switzerland) | 2021-08-17 |
| 467 | DRAEM — A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: These methods are trained only on anomaly-free images, and often require hand-crafted post-processing steps to localize the anomalies, which prohibits optimizing the feature extraction for maximal detection capability. |
Vitjan Zavrtanik; Matej Kristan; Danijel Skočaj; | arxiv-cs.CV | 2021-08-17 |
| 468 | Deep Convolutional Clustering-Based Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: This paper presents a novel approach for anomaly detection in industrial processes. The system solely relies on unlabeled data and employs a 1D-convolutional neural network-based … |
Gavneet Singh Chadha; Intekhab Islam; Andreas Schwung; Steven X Ding; | Sensors (Basel, Switzerland) | 2021-08-15 |
| 469 | Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this assumption, we propose a dynamic bipartite graph structure to encode the inter-dependencies between time-series. |
YUHANG WU et. al. | arxiv-cs.LG | 2021-08-15 |
| 470 | An Ensembled Anomaly Detector for Wafer Fault Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The production process of a wafer in the semiconductor industry consists of several phases such as a diffusion and associated defectivity test, parametric test, electrical wafer … |
GIUSEPPE FURNARI et. al. | Sensors (Basel, Switzerland) | 2021-08-13 |
| 471 | Masked Contrastive Learning for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a task-specific variant of contrastive learning named masked contrastive learning, which is more befitted for anomaly detection. |
Hyunsoo Cho; Jinseok Seol; Sang-goo Lee; | ijcai | 2021-08-13 |
| 472 | Random Subspace Mixture Models for Interpretable Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new subspace-based method to construct probabilistic models for high-dimensional data and highlight its use in anomaly detection. |
Cetin Savkli; Catherine Schwartz; | arxiv-cs.LG | 2021-08-13 |
| 473 | Understanding The Effect of Bias in Deep Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we aim to understand the effect of a biased anomaly set on anomaly detection. Our study demonstrates scenarios in which the biased anomaly set can be useful or problematic, and provides a solid benchmark for future research. |
Ziyu Ye; Yuxin Chen; Haitao Zheng; | ijcai | 2021-08-13 |
| 474 | RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this problem, we propose a robust framework using collaborative autoencoders to jointly identify normal observations from the data while learning its feature representation. |
Boyang Liu; Ding Wang; Kaixiang Lin; Pang-Ning Tan; Jiayu Zhou; | ijcai | 2021-08-13 |
| 475 | Deep-Learning-Based Approach to Anomaly Detection Techniques for Large Acoustic Data in Machine Operation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: As the workforce shrinks, the demand for automatic, labor-saving, anomaly detection technology that can perform maintenance on advanced equipment such as vehicles has been … |
Hyojung Ahn; Inchoon Yeo; | Sensors (Basel, Switzerland) | 2021-08-12 |
| 476 | Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these challenges, in this paper, we propose OC4Seq, a multi-scale one-class recurrent neural network for detecting anomalies in discrete event sequences. |
ZHIWEI WANG et. al. | kdd | 2021-08-12 |
| 477 | Multivariate Time Series Anomaly Detection and Interpretation Using Hierarchical Inter-Metric and Temporal Embedding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose InterFusion, an unsupervised method that simultaneously models the inter-metric and temporal dependency for MTS. |
ZHIHAN LI et. al. | kdd | 2021-08-12 |
| 478 | Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose here instead a deep reinforcement learning-based approach that enables an end-to-end optimization of the detection of both labeled and unlabeled anomalies. |
Guansong Pang; Anton van den Hengel; Chunhua Shen; Longbing Cao; | kdd | 2021-08-12 |
| 479 | CPNet: Cross-Parallel Network for Efficient Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, Cross-Parallel Network (CPNet) for efficient anomaly detection is proposed here to minimize computations without performance drops. |
Youngsaeng Jin; Jonghwan Hong; David Han; Hanseok Ko; | arxiv-cs.CV | 2021-08-10 |
| 480 | Flow-based SVDD for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose FlowSVDD — a flow-based one-class classifier for anomaly/outliers detection that realizes a well-known SVDD principle using deep learning tools. |
MARCIN SENDERA et. al. | arxiv-cs.LG | 2021-08-10 |
| 481 | Transfer Learning Gaussian Anomaly Detection By Fine-tuning Representations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In our work, we propose a new method to overcome catastrophic forgetting and thus successfully fine-tune pre-trained representations for AD in the transfer learning setting. |
Oliver Rippel; Arnav Chavan; Chucai Lei; Dorit Merhof; | arxiv-cs.CV | 2021-08-09 |
| 482 | Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address this challenge by proposing an adaptive anomaly detection scheme with hierarchical edge computing (HEC). |
Mao V. Ngo; Tie Luo; Tony Q. S. Quek; | arxiv-cs.LG | 2021-08-09 |
| 483 | Autoencoders on FPGAs for Real-time, Unsupervised New Physics Detection at 40 MHz at The Large Hadron Collider IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). |
EKATERINA GOVORKOVA et. al. | arxiv-physics.ins-det | 2021-08-09 |
| 484 | Ensemble Neuroevolution Based Approach for Multivariate Time Series Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, a framework is shown which incorporates neuroevolution methods to boost the anomaly-detection scores of new and already known models. |
Kamil Faber; Dominik Żurek; Marcin Pietroń; Kamil Piętak; | arxiv-cs.LG | 2021-08-08 |
| 485 | Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering these two points together, we propose a novel anomaly detection framework for credit card fraud detection as well as a model-explaining module responsible for prediction explanations. |
Tungyu Wu; Youting Wang; | arxiv-cs.LG | 2021-08-05 |
| 486 | Log-based Anomaly Detection Without Log Parsing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the limitations of existing methods, we propose NeuralLog, a novel log-based anomaly detection approach that does not require log parsing. |
Van-Hoang Le; Hongyu Zhang; | arxiv-cs.SE | 2021-08-04 |
| 487 | Weakly Supervised Low-Rank Representation for Hyperspectral Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In this article, we propose a weakly supervised low-rank representation (WSLRR) method for hyperspectral anomaly detection (HAD), which formulates deep learning-based HAD into a … |
WEIYING XIE et. al. | IEEE transactions on cybernetics | 2021-08-04 |
| 488 | Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and evaluate P-AnoGAN, an unsupervised anomaly detection approach for lung nodules in radiographs. |
Nitish Bhatt; David Ramon Prados; Nedim Hodzic; Christos Karanassios; H. R. Tizhoosh; | arxiv-cs.CV | 2021-08-04 |
| 489 | Explainable Deep Few-shot Anomaly Detection with Deviation Networks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we introduce a novel weakly-supervised anomaly detection framework to train detection models without assuming the examples illustrating all possible classes of anomaly. |
Guansong Pang; Choubo Ding; Chunhua Shen; Anton van den Hengel; | arxiv-cs.CV | 2021-08-01 |
| 490 | Explainable Anomaly Detection Framework for Maritime Main Engine Sensor Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: In this study, we proposed a data-driven approach to the condition monitoring of the marine engine. Although several unsupervised methods in the maritime industry have existed, … |
Donghyun Kim; Gian Antariksa; Melia Putri Handayani; Sangbong Lee; Jihwan Lee; | Sensors (Basel, Switzerland) | 2021-07-31 |
| 491 | HR-Crime: Human-Related Anomaly Detection in Surveillance Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce HR-Crime, a subset of the UCF-Crime dataset suitable for human-related anomaly detection tasks. |
Kayleigh Boekhoudt; Alina Matei; Maya Aghaei; Estefanía Talavera; | arxiv-cs.CV | 2021-07-31 |
| 492 | Anomaly Detection with Neural Parsers That Never Reject Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, this also presents a limitation: because the trained neural network can successfully parse any sentence, it cannot be directly used to identify sentences that deviate from the format of the training sentences, i.e., that are anomalous. In this paper, we address this limitation by presenting procedures for extracting production rules from the neural network, and for using these rules to determine whether a given sentence is nominal or anomalous. |
Alexander Grushin; Walt Woods; | arxiv-cs.LG | 2021-07-30 |
| 493 | EvAn: Neuromorphic Event-Based Sparse Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: cameras are bio-inspired novel sensors that asynchronously record changes in illumination in the form of events. This principle results in significant advantages over conventional … |
Lakshmi Annamalai; Anirban Chakraborty; Chetan Singh Thakur; | Frontiers in neuroscience | 2021-07-29 |
| 494 | Convolutional Transformer Based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose Convolutional Transformer based Dual Discriminator Generative Adversarial Networks (CT-D2GAN) to perform unsupervised video anomaly detection. |
XINYANG FENG et. al. | arxiv-cs.CV | 2021-07-28 |
| 495 | Fast Wireless Sensor Anomaly Detection Based on Data Stream in Edge Computing Enabled Smart Greenhouse Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Considering these issues, a novel method (called DLSHiForest) on basis of Locality-Sensitive Hashing and time window technique in this paper is proposed to solve these problems while achieving accurate and efficient detection. |
YIHONG YANG et. al. | arxiv-cs.LG | 2021-07-28 |
| 496 | Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signals Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel deep learning-based anomaly detection algorithm called Deep Convolutional Autoencoding Memory network (CAE-M). |
Yuxin Zhang; Yiqiang Chen; Jindong Wang; Zhiwen Pan; | arxiv-cs.AI | 2021-07-27 |
| 497 | Discriminative-Generative Representation Learning for One-Class Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to improve the representation learning ability of generator, we propose a self-supervised learning framework combining generative methods and discriminative methods. |
XUAN XIA et. al. | arxiv-cs.CV | 2021-07-27 |
| 498 | CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization Via Conditional Normalizing Flows Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a real-time model and analytically derive its relationship to prior methods. |
Denis Gudovskiy; Shun Ishizaka; Kazuki Kozuka; | arxiv-cs.CV | 2021-07-26 |
| 499 | Anomaly Detection in Videos Using Two-Stream Autoencoder with Post Hoc Interpretability Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The growing interest in deep learning approaches to video surveillance raises concerns about the accuracy and efficiency of neural networks. However, fast and reliable detection … |
Jiangfan Feng; Yukun Liang; Lin Li; | Computational intelligence and neuroscience | 2021-07-26 |
| 500 | Tail of Distribution GAN (TailGAN): Generative-Adversarial-Network-Based Boundary Formation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we create a GAN-based tail formation model for anomaly detection, the Tail of distribution GAN (TailGAN), to generate samples on the tail of the data distribution and detect anomalies near the support boundary. |
Nikolaos Dionelis; Mehrdad Yaghoobi; Sotirios A. Tsaftaris; | arxiv-cs.LG | 2021-07-24 |
| 501 | Two Class Pruned Log Message Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Log messages are widely used in cloud servers and other systems. Millions of logs are generated each day which makes them important for anomaly detection. However, they are … |
Amir Farzad; T Aaron Gulliver; | SN computer science | 2021-07-24 |
| 502 | HURRA! Human Readable Router Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents HURRA, a system that aims to reduce the time spent by human operators in the process of network troubleshooting. |
Jose M. Navarro; Dario Rossi; | arxiv-cs.AI | 2021-07-23 |
| 503 | Multi-Perspective Content Delivery Networks Security Framework Using Optimized Unsupervised Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a multi-perspective unsupervised learning framework for anomaly detection in CDNs. |
LI YANG et. al. | arxiv-cs.CR | 2021-07-23 |
| 504 | Probabilistic Forecast Combination for Anomaly Detection in Building Heat Load Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose to employ a probabilistic forecast combination approach based on an ensemble of deterministic forecasts in an anomaly detection scheme that classifies observed values based on their probability under a predictive distribution. |
Mario Beykirch; Tim Janke; Imed Tayeche; Florian Steinke; | arxiv-stat.AP | 2021-07-22 |
| 505 | Using UMAP to Inspect Audio Data for Unsupervised Anomaly Detection Under Domain-Shift Conditions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the difficulties encountered in the UAD-S task presented at the 2021 edition of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, we visually inspect Uniform Manifold Approximations and Projections (UMAPs) for log-STFT, log-mel and pretrained Look, Listen and Learn (L3) representations of the DCASE UAD-S dataset. |
Andres Fernandez; Mark D. Plumbley; | arxiv-cs.SD | 2021-07-22 |
| 506 | Anomaly Detection Via Self-organizing Map Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel unsupervised anomaly detection approach based on Self-organizing Map (SOM). |
NING LI et. al. | arxiv-cs.CV | 2021-07-21 |
| 507 | Canonical Polyadic Decomposition and Deep Learning for Machine Fault Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a powerful data-driven and quasi non-parametric denoising strategy for spectral data based on a tensor decomposition: the Non-negative Canonical Polyadic (CP) decomposition. |
Frusque Gaetan; Michau Gabriel; Fink Olga; | arxiv-stat.ML | 2021-07-20 |
| 508 | A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper we investigate different methods of deep learning, including supervised and unsupervised learning, for anomaly detection applied to a quality assurance use case. |
Vincent Wilmet; Sauraj Verma; Tabea Redl; Håkon Sandaker; Zhenning Li; | arxiv-cs.CV | 2021-07-19 |
| 509 | PICASO: Permutation-Invariant Cascaded Attentional Set Operator Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this limitation, we propose a permutation-invariant cascaded attentional set operator (PICASO). |
Samira Zare; Hien Van Nguyen; | arxiv-cs.CV | 2021-07-17 |
| 510 | Contrastive Predictive Coding for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we close this gap by making use of the Contrastive Predictive Coding model (arXiv:1807.03748). |
Puck de Haan; Sindy Löwe; | arxiv-cs.CV | 2021-07-16 |
| 511 | Neural Contextual Anomaly Detection for Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts 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; | arxiv-cs.LG | 2021-07-16 |
| 512 | Metro Passenger-Flow Representation Via Dynamic Mode Decomposition and Its Application Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Passenger-flow anomaly detection and prediction are essential tasks for intelligent operation of the metro system. Accurate passenger-flow representation is the foundation of … |
XIULAN WEI et. al. | IEEE transactions on neural networks and learning systems | 2021-07-16 |
| 513 | OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Human operators often diagnose industrial machinery via anomalous sounds. Given the new advances in the field of machine learning, automated acoustic anomaly detection can lead to … |
Saad Abbasi; Mahmoud Famouri; Mohammad Javad Shafiee; Alexander Wong; | Sensors (Basel, Switzerland) | 2021-07-14 |
| 514 | Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To better understand the characteristics of different anomaly detectors, in this paper, we provide a comprehensive review and evaluation of five popular neural networks used by six state-of-the-art methods. |
Zhuangbin Chen; Jinyang Liu; Wenwei Gu; Yuxin Su; Michael R. Lyu; | arxiv-cs.SE | 2021-07-13 |
| 515 | Decoupling Representation Learning and Classification for GNN-based Anomaly Detection IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To be less biased by the inconsistency, we propose a simple yet effective graph SSL scheme, called Deep Cluster Infomax (DCI) for node representation learning, which captures the intrinsic graph properties in more concentrated feature spaces by clustering the entire graph into multiple parts. |
YANLING WANG et. al. | sigir | 2021-07-13 |
| 516 | Anomaly Detection in Smart Manufacturing with An Application Focus on Robotic Finishing Systems: A Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an overview of the components, benefits, challenges, methods, and open problems of anomaly detection in smart manufacturing and robotic finishing systems are discussed. |
Tareq Tayeh; Abdallah Shami; | arxiv-cs.RO | 2021-07-11 |
| 517 | Anomaly Detection in Residential Video Surveillance on Edge Devices in IoT Framework Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we propose anomaly detection for intelligent surveillance using CPU-only edge devices. |
Mayur R. Parate; Kishor M. Bhurchandi; Ashwin G. Kothari; | arxiv-cs.CV | 2021-07-10 |
| 518 | Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: So motivated, we propose a conceptually simple entrywise approach to anomaly detection in low-rank matrices. |
Vivek Farias; Andrew A Li; Tianyi Peng; | icml | 2021-07-08 |
| 519 | Transfer-Based Semantic Anomaly Detection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that a previously overlooked strategy for anomaly detection (AD) is to introduce an explicit inductive bias toward representations transferred over from some large and varied semantic task. |
Lucas Deecke; Lukas Ruff; Robert A. Vandermeulen; Hakan Bilen; | icml | 2021-07-08 |
| 520 | A General Framework For Detecting Anomalous Inputs to DNN Classifiers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an unsupervised anomaly detection framework based on the internal DNN layer representations in the form of a meta-algorithm with configurable components. |
Jayaram Raghuram; Varun Chandrasekaran; Somesh Jha; Suman Banerjee; | icml | 2021-07-08 |
| 521 | Anomaly Detection Using Edge Computing in Video Surveillance System: Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we surveyed various methodologies developed to detect anomalies in intelligent video surveillance. |
Devashree R. Patrikar; Mayur Rajram Parate; | arxiv-cs.CV | 2021-07-06 |
| 522 | Detecting Outliers with Poisson Image Interpolation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an alternative to image reconstruction-based and image embedding-based methods and propose a new self-supervised method to tackle pathological anomaly detection. |
JEREMY TAN et. al. | arxiv-cs.CV | 2021-07-06 |
| 523 | New Methods and Datasets for Group Anomaly Detection From Fundamental Physics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Then we propose a realistic synthetic benchmark dataset (LHCO2020) for the development of group anomaly detection algorithms. |
Gregor Kasieczka; Benjamin Nachman; David Shih; | arxiv-stat.ML | 2021-07-06 |
| 524 | A Typology of Data Anomalies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper therefore introduces a general typology of anomalies that offers a clear and tangible definition of the different types of anomalies in datasets. |
Ralph Foorthuis; | arxiv-cs.LG | 2021-07-04 |
| 525 | Using Progressive Context Encoders for Anomaly Detection in Digital Pathology Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we combine progressive generative adversarial networks with a flexible adversarial autoencoder architecture capable of learning the normal distribution of WSIs of normal skin tissue at extremely high resolution and demonstrate its anomaly detection performance. |
R. GILLARD et. al. | bio.pathology | 2021-07-04 |
| 526 | A Collective Anomaly Detection Method Over Bitcoin Network Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The main purpose of this study is to present a new method for detecting anomalies in Bitcoin with more appropriate efficiency. |
Mohammad Javad Shayegan; Hamid Reza Sabor; | arxiv-cs.CR | 2021-07-02 |
| 527 | A Weakly Supervised Gas-Path Anomaly Detection Method for Civil Aero-Engines Based on Mapping Relationship Mining of Gas-Path Parameters and Improved Density Peak Clustering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Gas-path anomalies account for more than 90% of all civil aero-engine anomalies. It is essential to develop accurate gas-path anomaly detection methods. Therefore, a weakly … |
Hao Sun; Xuyun Fu; Shisheng Zhong; | Sensors (Basel, Switzerland) | 2021-07-01 |
| 528 | Interpretable Anomaly Detection in Event Sequences Via Sequence Matching and Visual Comparison Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the majority of a dataset. When analyzing event … |
SHUNAN GUO et. al. | IEEE transactions on visualization and computer graphics | 2021-06-30 |
| 529 | One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a general-purpose application for steel anomaly detection that consists of the following four components. |
Takato Yasuno; Junichiro Fujii; Sakura Fukami; | arxiv-cs.CV | 2021-06-30 |
| 530 | Anomaly Detection: How to Artificially Increase Your F1-Score with A Biased Evaluation Protocol Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that F1-score and AVPR are highly sensitive to the contamination rate. |
Damien Fourure; Muhammad Usama Javaid; Nicolas Posocco; Simon Tihon; | arxiv-cs.LG | 2021-06-30 |
| 531 | SDFVAE: Static and Dynamic Factorized VAE for Anomaly Detection of Multivariate CDN KPIs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a robust and noise-resilient anomaly detection mechanism using multivariate KPIs. |
LIANG DAI et. al. | www | 2021-06-25 |
| 532 | Few-shot Network Anomaly Detection Via Cross-network Meta-learning IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Taking advantage of this potential, in this work, we tackle the problem of few-shot network anomaly detection by (1) proposing a new family of graph neural networks – Graph Deviation Networks (GDN) that can leverage a small number of labeled anomalies for enforcing statistically significant deviations between abnormal and normal nodes on a network; and (2) equipping the proposed GDN with a new cross-network meta-learning algorithm to realize few-shot network anomaly detection by transferring meta-knowledge from multiple auxiliary networks. |
Kaize Ding; Qinghai Zhou; Hanghang Tong; Huan Liu; | www | 2021-06-25 |
| 533 | AURORA: A Unified FRamework FOR Anomaly Detection on Multivariate Time Series Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The ability to accurately and consistently discover anomalies in time series is important in many applications. Fields such as finance (fraud detection), information security … |
LIN ZHANG et. al. | Data mining and knowledge discovery | 2021-06-23 |
| 534 | Detecting Anomalous User Behavior in Remote Patient Monitoring Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an anomaly detection model for RPM utilizing IoMT and smart home devices. |
Deepti Gupta; Maanak Gupta; Smriti Bhatt; |