Paper Digest: Recent Papers on Anomaly Detection
Paper Digest Team extracted all recent Anomaly Detection related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Anomaly Detection
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Long-lived Particles Anomaly Detection with Parametrized Quantum Circuits Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an anomaly detection algorithm based on a parametrized quantum circuit. |
Simone Bordoni; Denis Stanev; Tommaso Santantonio; Stefano Giagu; | arxiv-quant-ph | 2023-12-07 |
| 2 | Multimodal Industrial Anomaly Detection By Crossmodal Feature Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a novel light and fast framework that learns to map features from one modality to the other on nominal samples. |
Alex Costanzino; Pierluigi Zama Ramirez; Giuseppe Lisanti; Luigi Di Stefano; | arxiv-cs.CV | 2023-12-07 |
| 3 | Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the Adversarial Denoising Diffusion Model (ADDM). |
Jongmin Yu; Hyeontaek Oh; Jinhong Yang; | arxiv-eess.IV | 2023-12-07 |
| 4 | Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, the presence of anomalies in lane rendering map images occasionally introduces potential hazards, as such anomalies can be misleading to human drivers and consequently contribute to unsafe driving conditions. In response to this concern and to accurately and effectively detect the anomalies, this paper transforms lane rendering image anomaly detection into a classification problem and proposes a four-phase pipeline consisting of data pre-processing, self-supervised pre-training with the masked image modeling (MiM) method, customized fine-tuning using cross-entropy based loss with label smoothing, and post-processing to tackle it leveraging state-of-the-art deep learning techniques, especially those involving Transformer models. |
YONGQI DONG et. al. | arxiv-cs.CV | 2023-12-07 |
| 5 | Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they face challenges in preserving intensity characteristics in the reconstructed images, limiting their performance in anomaly detection. To address this challenge, we propose to condition the denoising mechanism of diffusion models with additional information about the image to reconstruct coming from a latent representation of the noise-free input image. |
FINN BEHRENDT et. al. | arxiv-eess.IV | 2023-12-07 |
| 6 | Learning Cortical Anomaly Through Masked Encoding for Unsupervised Heterogeneity Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces CAM (Cortical Anomaly Detection through Masked Image Modeling), a novel self-supervised framework designed for the unsupervised detection of complex brain disorders using cortical surface features. |
HAO-CHUN YANG et. al. | arxiv-eess.IV | 2023-12-05 |
| 7 | Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike other reconstruction-based methods, we present a novel self-supervised masked convolutional transformer block (SSMCTB) that comprises the reconstruction-based functionality at a core architectural level. |
NEELU MADAN et. al. | IEEE transactions on pattern analysis and machine … | 2023-12-05 |
| 8 | Pseudo Replay-based Class Continual Learning for Online New Category Anomaly Detection in Additive Manufacturing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Among all continual learning methods, memory-based continual learning has the best performance but faces the constraints of data storage capacity. To address this issue, this paper develops a novel pseudo replay-based continual learning by integrating class incremental learning and oversampling-based data generation. |
Zhangyue Shi; Tianxin Xie; Chenang Liu; Yuxuan Li; | arxiv-cs.LG | 2023-12-04 |
| 9 | Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, these studies usually just detect the most abnormal segments, potentially overlooking the completeness of anomalies. To address these limitations, we propose a Dynamic Erasing Network (DE-Net) for weakly supervised video anomaly detection, which learns multi-scale temporal features. |
CHEN ZHANG et. al. | arxiv-cs.CV | 2023-12-04 |
| 10 | EdgeConvFormer: Dynamic Graph CNN and Transformer Based Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, Transformer-based anomaly detection models have problems such as a large amount of data being required for training, standard positional encoding is not suitable for multivariate time series data, and the interdependence between time series is not considered. To address these limitations, we propose a novel anomaly detection method, named EdgeConvFormer, which integrates Time2vec embedding, stacked dynamic graph CNN, and Transformer to extract global and local spatial-time information. |
Jie Liu; Qilin Li; Senjian An; Bradley Ezard; Ling Li; | arxiv-cs.LG | 2023-12-04 |
| 11 | ADT: Agent-based Dynamic Thresholding for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we model thresholding in anomaly detection as a Markov Decision Process and propose an agent-based dynamic thresholding (ADT) framework based on a deep Q-network. |
Xue Yang; Enda Howley; Micheal Schukat; | arxiv-cs.LG | 2023-12-03 |
| 12 | Revisiting Non-separable Binary Classification and Its Applications in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead of separating data between halfspaces, we propose a slightly different paradigm, equality separation, that adapts the SVM objective to distinguish data within or outside the margin. |
Matthew Lau; Ismaila Seck; Athanasios P Meliopoulos; Wenke Lee; Eugene Ndiaye; | arxiv-cs.LG | 2023-12-03 |
| 13 | Bagged Regularized $k$-Distances for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new distance-based algorithm called bagged regularized $k$-distances for anomaly detection (BRDAD) converting the unsupervised anomaly detection problem into a convex optimization problem. |
Yuchao Cai; Yuheng Ma; Hanfang Yang; Hanyuan Hang; | arxiv-stat.ML | 2023-12-02 |
| 14 | Anomaly Detection in Collider Physics Via Factorized Observables Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a new anomaly detection strategy called FORCE: factorized observables for regressing conditional expectations. |
Eric M. Metodiev; Jesse Thaler; Raymond Wynne; | arxiv-hep-ph | 2023-11-30 |
| 15 | Unsupervised Multimodal Anomaly Detection With Missing Sources for Liquid Rocket Engine Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: 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 | 2023-11-30 |
| 16 | TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces TransNAS-TSAD, a novel framework that synergizes transformer architecture with neural architecture search (NAS), enhanced through NSGA-II algorithm optimization. |
Ijaz Ul Haq; Byung Suk Lee; | arxiv-cs.LG | 2023-11-29 |
| 17 | Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present Set-VAE, a particle-based variational autoencoder (VAE) anomaly detection algorithm. |
Ryan Liu; Abhijith Gandrakota; Jennifer Ngadiuba; Maria Spiropulu; Jean-Roch Vlimant; | arxiv-hep-ex | 2023-11-28 |
| 18 | Diagnosis Driven Anomaly Detection for CPS Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, anomaly detection and diagnosis must be developed together to provide a holistic solution for diagnosis in CPS. We therefore propose a method for utilizing deep learning-based anomaly detection to generate inputs for Consistency-Based Diagnosis (CBD). |
Henrik S. Steude; Lukas Moddemann; Alexander Diedrich; Jonas Ehrhardt; Oliver Niggemann; | arxiv-cs.LG | 2023-11-27 |
| 19 | DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unsupervised Anomaly Detection (UAD) techniques aim to identify and localize anomalies without relying on annotations, only leveraging a model trained on a dataset known to be free of anomalies. |
SERGIO NAVAL MARIMONT et. al. | arxiv-cs.CV | 2023-11-26 |
| 20 | BatchNorm-based Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Inspired by the statistical insight that temporal features of abnormal events often exhibit outlier characteristics, we propose a novel method, BN-WVAD, which incorporates BatchNorm into WVAD. |
YIXUAN ZHOU et. al. | arxiv-cs.CV | 2023-11-26 |
| 21 | Fault Detection in Telecom Networks Using Bi-level Federated Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Bi-level Federated Graph Neural Network anomaly detection and diagnosis model that is able to detect anomalies in Telecom networks in a privacy-preserving manner, while minimizing communication costs. |
R. Bourgerie; T. Zanouda; | arxiv-cs.LG | 2023-11-24 |
| 22 | Towards Scalable 3D Anomaly Detection and Localization: A Benchmark Via 3D Anomaly Synthesis and A Self-Supervised Learning Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To enable scalable anomaly data collection, we propose a 3D anomaly synthesis pipeline to adapt existing large-scale 3Dmodels for 3D anomaly detection. |
WENQIAO LI et. al. | arxiv-cs.CV | 2023-11-24 |
| 23 | Multi-Class Anomaly Detection Based on Regularized Discriminative Coupled Hypersphere-based Feature Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a new model by including class discriminative properties obtained by a modified Regularized Discriminative Variational Auto-Encoder (RD-VAE) in the feature extraction process of Coupled-hypersphere-based Feature Adaptation (CFA). |
Mehdi Rafiei; Alexandros Iosifidis; | arxiv-cs.CV | 2023-11-24 |
| 24 | Non-resonant Anomaly Detection with Background Extrapolation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we extend a class of weakly supervised anomaly detection strategies developed for resonant physics to the non-resonant case. |
Kehang Bai; Radha Mastandrea; Benjamin Nachman; | arxiv-hep-ph | 2023-11-21 |
| 25 | Diffusion MRI Anomaly Detection in Glioma Patients Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We hypothesized that dMRI is well suited for tumor delineation, and developed two different deep-learning approaches. |
LEON WENINGER et. al. | Scientific reports | 2023-11-21 |
| 26 | Explainable Anomaly Detection Using Masked Latent Generative Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel time series anomaly detection method that achieves excellent detection accuracy while offering a superior level of explainability. |
Daesoo Lee; Sara Malacarne; Erlend Aune; | arxiv-cs.LG | 2023-11-21 |
| 27 | Magnetic Anomaly Detection Based on A Compound Tri-Stable Stochastic Resonance System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the problem of severe system parameter coupling in a conventional tri-stable stochastic resonance model leads to difficulty in potential function regulation. In this paper, a new compound tri-stable stochastic resonance (CTSR) model is proposed to address this problem by combining a Gaussian Potential model and the mixed bi-stable model. |
JINBO HUANG et. al. | Sensors (Basel, Switzerland) | 2023-11-20 |
| 28 | A Method for Image Anomaly Detection Based on Distillation and Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an image anomaly detection algorithm based on feature distillation and an autoencoder structure, which uses the feature distillation structure of a dual-teacher network to train the encoder, thus suppressing the reconstruction of abnormal regions. |
Jiaxiang Luo; Jianzhao Zhang; | Sensors (Basel, Switzerland) | 2023-11-20 |
| 29 | NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, rather than proposing a new semi-supervised or supervised approach for AD, we introduce a novel algorithm for generating additional pseudo-anomalies on the basis of the limited labeled anomalies and a large volume of unlabeled data. |
Hao Dong; Gaëtan Frusque; Yue Zhao; Eleni Chatzi; Olga Fink; | arxiv-cs.LG | 2023-11-20 |
| 30 | LogLead — Fast and Integrated Log Loader, Enhancer, and Anomaly Detector Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces LogLead, a tool designed for efficient log analysis. |
Mika Mäntylä; Yuqing Wang; Jesse Nyyssölä; | arxiv-cs.SE | 2023-11-20 |
| 31 | Anomaly Detection in Time Series Data Using Reversible Instance Normalized Anomaly Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we use the rarity of anomalies to detect them. For this, we introduce the reversible instance normalized anomaly transformer (RINAT). |
Ranjai Baidya; Heon Jeong; | Sensors (Basel, Switzerland) | 2023-11-19 |
| 32 | Unraveling The Anomaly in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This problem is exacerbated by ill-posed evaluation metrics, known as point adjustment (PA), which can result in inflated model performance. In this context, we propose a novel self-supervised learning based Tri-domain Anomaly Detector (TriAD), which addresses these challenges by modeling features across three data domains – temporal, frequency, and residual domains – without relying on anomaly labels. |
YUTING SUN et. al. | arxiv-cs.LG | 2023-11-19 |
| 33 | SORTAD: Self-Supervised Optimized Random Transformations for Anomaly Detection in Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose SORTAD, a novel algorithm that is tailor-made to solve these challenges. |
Guy Hay; Pablo Liberman; | arxiv-cs.LG | 2023-11-18 |
| 34 | Maintenance Techniques for Anomaly Detection AIOps Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we analyze two different anomaly detection model maintenance techniques in terms of the model update frequency, namely blind model retraining and informed model retraining. |
Lorena Poenaru-Olaru; Natalia Karpova; Luis Cruz; Jan Rellermeyer; Arie van Deursen; | arxiv-cs.LG | 2023-11-17 |
| 35 | Few-shot Message-Enhanced Contrastive Learning for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In real-world scenarios, a limited batch of labeled anomalies can be captured, making it crucial to investigate the few-shot problem in graph anomaly detection. Taking advantage of this potential, we propose a novel few-shot Graph Anomaly Detection model called FMGAD (Few-shot Message-Enhanced Contrastive-based Graph Anomaly Detector). |
FAN XU et. al. | arxiv-cs.LG | 2023-11-17 |
| 36 | Weakly Supervised Anomaly Detection for Chest X-Ray Image Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For this purpose, we propose WSCXR, a weakly supervised anomaly detection framework for CXR. |
Haoqi Ni; Ximiao Zhang; Min Xu; Ning Lang; Xiuzhuang Zhou; | arxiv-eess.IV | 2023-11-16 |
| 37 | SVD-AE: An Asymmetric Autoencoder with SVD Regularization for Multivariate Time Series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection in multivariate time series is of critical importance in many real-world applications, such as system maintenance and Internet monitoring. In this article, we … |
Yueyue Yao; Jianghong Ma; Shanshan Feng; Yunming Ye; | Neural networks : the official journal of the International … | 2023-11-15 |
| 38 | Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome K -mers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper uses anomaly detection models to analyze SARS-CoV-2 virus genome -mers to predict possible new critical variants in the collected samples. |
Haotian Ren; Yixue Li; Tao Huang; | Microorganisms | 2023-11-15 |
| 39 | Correlation-Aware Spatial-Temporal Graph Learning for Multivariate Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing approaches for this problem mostly employ either statistical models which cannot capture the nonlinear relations well or conventional deep learning (DL) models e.g., convolutional neural network (CNN) and long short-term memory (LSTM) that do not explicitly learn the pairwise correlations among variables. To overcome these limitations, we propose a novel method, correlation-aware spatial-temporal graph learning (termed ), for time-series anomaly detection. |
YU ZHENG et. al. | IEEE transactions on neural networks and learning systems | 2023-11-14 |
| 40 | VegaEdge: Edge AI Confluence Anomaly Detection for Real-Time Highway IoT-Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With the surge of the Internet of Things (IoT) in recent years, there has arisen a pressing demand for Artificial Intelligence (AI) based anomaly detection methods designed to meet the requirements of IoT devices. Catering to this futuristic vision, we introduce a lightweight approach to vehicle anomaly detection by utilizing the power of trajectory prediction. |
Vinit Katariya; Fatema-E- Jannat; Armin Danesh Pazho; Ghazal Alinezhad Noghre; Hamed Tabkhi; | arxiv-cs.CV | 2023-11-13 |
| 41 | Open-Set Graph Anomaly Detection Via Normal Structure Regularisation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel open-set GAD approach, namely normal structure regularisation (NSReg), to leverage the rich normal graph structure embedded in the labelled nodes to tackle the aforementioned two issues. |
Qizhou Wang; Guansong Pang; Mahsa Salehi; Wray Buntine; Christopher Leckie; | arxiv-cs.LG | 2023-11-12 |
| 42 | Open-Vocabulary Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a model that decouples OVVAD into two mutually complementary tasks — class-agnostic detection and class-specific classification — and jointly optimizes both tasks. |
PENG WU et. al. | arxiv-cs.CV | 2023-11-12 |
| 43 | Dual-Branch Reconstruction Network for Industrial Anomaly Detection with RGB-D Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the above methods require a longer inference time and higher memory usage, which cannot meet the real-time requirements of the industry. To overcome these issues, we propose a lightweight dual-branch reconstruction network(DBRN) based on RGB-D input, learning the decision boundary between normal and abnormal examples. |
Chenyang Bi; Yueyang Li; Haichi Luo; | arxiv-cs.CV | 2023-11-12 |
| 44 | CL-Flow:Strengthening The Normalizing Flows By Contrastive Learning for Better Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Considering the reasons mentioned above, we propose a self-supervised anomaly detection approach that combines contrastive learning with 2D-Flow to achieve more precise detection outcomes and expedited inference processes. |
Shunfeng Wang; Yueyang Li; Haichi Luo; Chenyang Bi; | arxiv-cs.IR | 2023-11-12 |
| 45 | Interpretable Graph Anomaly Detection Using Gradient Attention Maps Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach to graph anomaly detection that leverages the power of interpretability to enhance performance. |
Yifei Yang; Peng Wang; Xiaofan He; Dongmian Zou; | arxiv-cs.LG | 2023-11-10 |
| 46 | High-quality Semi-supervised Anomaly Detection with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, StyleGAN2 with adaptive discriminator augmentation (StyleGAN2-ADA), which can generate high-resolution and high-quality images with limited number of datasets, was used as the image generation model, and pixel-to-style-to-pixel (pSp) encoder was used to convert images into intermediate latent variables. |
Yuki Sato; Junya Sato; Noriyuki Tomiyama; Shoji Kido; | International journal of computer assisted radiology and … | 2023-11-09 |
| 47 | RAPID: Training-free Retrieval-based Log Anomaly Detection with PLM Considering Token-level Information Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce RAPID, a model that capitalizes on the inherent features of log data to enable anomaly detection without training delays, ensuring real-time capability. |
Gunho No; Yukyung Lee; Hyeongwon Kang; Pilsung Kang; | arxiv-cs.LG | 2023-11-09 |
| 48 | The Voraus-AD Dataset for Anomaly Detection in Robot Applications Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a dataset that allows training and benchmarking of anomaly detection methods for robotic applications based on machine data which will be made publicly available to the research community. |
Jan Thieß Brockmann; Marco Rudolph; Bodo Rosenhahn; Bastian Wandt; | arxiv-cs.RO | 2023-11-08 |
| 49 | Quantum-inspired Anomaly Detection, A QUBO Formulation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With the advent of quantum computing, there has been a growing interest in developing quantum approaches to anomaly detection. After reviewing traditional approaches to anomaly detection relying on statistical or distance-based methods, we will propose a Quadratic Unconstrained Binary Optimization (QUBO) model formulation of anomaly detection, compare it with classical methods, and discuss its scalability on current Quantum Processing Units (QPU). |
Julien Mellaerts; | arxiv-quant-ph | 2023-11-06 |
| 50 | Temporal Shift — Multi-Objective Loss Function for Improved Anomaly Fall Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new multi-objective loss function called Temporal Shift, which aims to predict both future and reconstructed frames within a window of sequential frames. |
Stefan Denkovski; Shehroz S. Khan; Alex Mihailidis; | arxiv-cs.CV | 2023-11-05 |
| 51 | Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The emergence of these often rarely occurring defect patterns explains the general need for labeled data corpora. To alleviate this issue and advance the current state of the art in unsupervised visual inspection, this work proposes a DifferNet-based solution enhanced with attention modules: AttentDifferNet. |
ANDRÉ LUIZ BUARQUE VIEIRA E SILVA et. al. | arxiv-cs.CV | 2023-11-05 |
| 52 | Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes The Lead Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study explores the use of GPT-4V(ision), a powerful visual-linguistic model, to address anomaly detection tasks in a generic manner. |
Yunkang Cao; Xiaohao Xu; Chen Sun; Xiaonan Huang; Weiming Shen; | arxiv-cs.CV | 2023-11-05 |
| 53 | Adversarial Data Augmentation for HMM-Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a data augmentation and retraining approach based on adversarial learning for improving anomaly detection. |
Alberto Castellini; Francesco Masillo; Davide Azzalini; Francesco Amigoni; Alessandro Farinelli; | IEEE transactions on pattern analysis and machine … | 2023-11-03 |
| 54 | Triggerless Data Acquisition Pipeline for Machine Learning Based Statistical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from a particle detector. |
GAIA GROSSO et. al. | arxiv-hep-ex | 2023-11-03 |
| 55 | Holistic Representation Learning for Multitask Trajectory Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a holistic representation of skeleton trajectories to learn expected motions across segments at different times. |
Alexandros Stergiou; Brent De Weerdt; Nikos Deligiannis; | arxiv-cs.CV | 2023-11-03 |
| 56 | Respiratory Anomaly Detection Using Reflected Infrared Light-wave Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we present a non-contact respiratory anomaly detection method using incoherent light-wave signals reflected from the chest of a mechanical robot that can breathe like human beings. |
MD ZOBAER ISLAM et. al. | arxiv-eess.SP | 2023-11-02 |
| 57 | Time Series Anomaly Detection Using Diffusion-based Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Diffusion models have been recently used for anomaly detection (AD) in images. In this paper we investigate whether they can also be leveraged for AD on multivariate time series (MTS). |
Ioana Pintilie; Andrei Manolache; Florin Brad; | arxiv-cs.LG | 2023-11-02 |
| 58 | Cheating Depth: Enhancing 3D Surface Anomaly Detection Via Depth Simulation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: (i) We propose a novel Depth-Aware Discrete Autoencoder (DADA) architecture, that enables learning a general discrete latent space that jointly models RGB and 3D data for 3D surface anomaly detection. |
Vitjan Zavrtanik; Matej Kristan; Danijel Skočaj; | arxiv-cs.CV | 2023-11-02 |
| 59 | Anomaly Detection in The Production Process of Stamping Progressive Dies Using The Shape- and Size-Adaptive Descriptors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the production process of progressive die stamping, anomaly detection is essential for ensuring the safety of expensive dies and the continuous stability of the production … |
Liang Ma; Fanwu Meng; | Sensors (Basel, Switzerland) | 2023-11-01 |
| 60 | Architecture of Data Anomaly Detection-Enhanced Decentralized Expert System for Early-Stage Alzheimer’s Disease Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a groundbreaking decentralized expert system that cleverly combines blockchain technology with Artificial Intelligence (AI) to integrate robust anomaly detection for patient-submitted data. |
Stefan Kambiz Behfar; Qumars Behfar; Marzie Hosseinpour; | arxiv-cs.CR | 2023-11-01 |
| 61 | Log-based Anomaly Detection of Enterprise Software: An Empirical Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we evaluate several state-of-the-art anomaly detection models on an industrial dataset from our research partner, which is much smaller and loosely structured than most large scale open-source benchmark datasets. |
Nadun Wijesinghe; Hadi Hemmati; | arxiv-cs.LG | 2023-10-31 |
| 62 | AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we introduce a novel approach, namely AnomalyCLIP, to adapt CLIP for accurate ZSAD across different domains. |
Qihang Zhou; Guansong Pang; Yu Tian; Shibo He; Jiming Chen; | arxiv-cs.CV | 2023-10-29 |
| 63 | Myriad: Large Multimodal Model By Applying Vision Experts for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel large multi-modal model by applying vision experts for industrial anomaly detection (dubbed Myriad), which leads to definite anomaly detection and high-quality anomaly description. |
YUANZE LI et. al. | arxiv-cs.CV | 2023-10-29 |
| 64 | Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new method of training energy-based models (EBMs) for anomaly detection that leverages low-dimensional structures within data. |
Sangwoong Yoon; Young-Uk Jin; Yung-Kyun Noh; Frank C. Park; | arxiv-cs.LG | 2023-10-28 |
| 65 | Hyperspectral Anomaly Detection With Tensor Average Rank and Piecewise Smoothness Constraints IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we develop a tensor-based anomaly detection algorithm that can effectively preserve the spatial-spectral information of the original data. |
Siyu Sun; Jun Liu; Xun Chen; Wei Li; Hongbin Li; | IEEE transactions on neural networks and learning systems | 2023-10-27 |
| 66 | Adversarial Anomaly Detection Using Gaussian Priors and Nonlinear Anomaly Scores Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: By combining the generative stability of a $\beta$-variational autoencoder (VAE) with the discriminative strengths of generative adversarial networks (GANs), we propose a novel model, $\beta$-VAEGAN. |
Fiete Lüer; Tobias Weber; Maxim Dolgich; Christian Böhm; | arxiv-cs.LG | 2023-10-27 |
| 67 | MEDAVET: Traffic Vehicle Anomaly Detection Mechanism Based on Spatial and Temporal Structures in Vehicle Traffic Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper aims to model vehicle tracking using computer vision to detect traffic anomalies on a highway. |
ANA ROSALÍA HUAMÁN REYNA et. al. | arxiv-cs.CV | 2023-10-27 |
| 68 | Making The End-User A Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose OrionBench — a user centric continuously maintained benchmark for unsupervised time series anomaly detection. |
Sarah Alnegheimish; Laure Berti-Equille; Kalyan Veeramachaneni; | arxiv-cs.LG | 2023-10-26 |
| 69 | A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This is because the lack of any ground truth annotations significantly increases the magnitude of the VAD challenge. To address this challenge, we propose a simple-but-effective two-stage pseudo-label generation framework that produces segment-level (normal/anomaly) pseudo-labels, which can be further used to train a segment-level anomaly detector in a supervised manner. |
Anas Al-lahham; Nurbek Tastan; Zaigham Zaheer; Karthik Nandakumar; | arxiv-cs.CV | 2023-10-26 |
| 70 | Anomaly Detection Using An Ensemble of Multi-Point LSTMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As technologies for storing time-series data such as smartwatches and smart factories become common, we are collectively accumulating a great deal of time-series data. With the … |
Geonseok Lee; Youngju Yoon; Kichun Lee; | Entropy (Basel, Switzerland) | 2023-10-26 |
| 71 | CHP Engine Anomaly Detection Based on Parallel CNN-LSTM with Residual Blocks and Attention Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The extreme operating environment of the combined heat and power (CHP) engine is likely to cause anomalies and defects, which can lead to engine failure; thus, detecting engine … |
Won Hee Chung; Yeong Hyeon Gu; Seong Joon Yoo; | Sensors (Basel, Switzerland) | 2023-10-26 |
| 72 | Towards Self-Interpretable Graph-Level Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate a new challenging problem, explainable GLAD, where the learning objective is to predict the abnormality of each graph sample with corresponding explanations, i.e., the vital subgraph that leads to the predictions. |
YIXIN LIU et. al. | arxiv-cs.LG | 2023-10-25 |
| 73 | On Pixel-level Performance Assessment in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Commonly adopted evaluation metrics designed for pixel-level detection may not effectively capture the nuanced performance variations arising from this class imbalance. In this paper, we dissect the intricacies of this challenge, underscored by visual evidence and statistical analysis, leading to delve into the need for evaluation metrics that account for the imbalance. |
Mehdi Rafiei; Toby P. Breckon; Alexandros Iosifidis; | arxiv-cs.CV | 2023-10-25 |
| 74 | PAD: A Dataset and Benchmark for Pose-agnostic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we build MAD using 20 complex-shaped LEGO toys including 4k views with various poses, and high-quality and diverse 3D anomalies in both simulated and real environments. |
QIANG ZHOU et. al. | nips | 2023-10-24 |
| 75 | Interpreting Unsupervised Anomaly Detection in Security Via Rule Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a post-hoc method to globally explain a black-box unsupervised anomaly detection model via rule extraction. |
Ruoyu Li; Qing Li; Yu Zhang; Dan Zhao; Yong Jiang; | nips | 2023-10-24 |
| 76 | Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a new method of training energy-based models (EBMs) for anomaly detection that leverages low-dimensional structures within data. |
Sangwoong Yoon; Young-Uk Jin; Yung-Kyun Noh; Frank Park; | nips | 2023-10-24 |
| 77 | Zero-Shot Batch-Level Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a simple yet effective method called Adaptive Centered Representations (ACR) for zero-shot batch-level AD. |
AODONG LI et. al. | nips | 2023-10-24 |
| 78 | Unsupervised Anomaly Detection with Rejection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, selecting a proper metric and setting the rejection threshold without labels are challenging tasks. In this paper, we solve these challenges by setting a constant rejection threshold on the stability metric computed by ExCeeD. |
Lorenzo Perini; Jesse Davis; | nips | 2023-10-24 |
| 79 | Truncated Affinity Maximization for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, this anomaly-discriminative property is ignored by existing GAD methods that are typically built using a conventional anomaly detection objective, such as data reconstruction. In this work, we explore this property to introduce a novel unsupervised anomaly scoring measure for GAD – local node affinity – that assigns a larger anomaly score to nodes that are less affiliated with their neighbors, with the affinity defined as similarity on node attributes/representations. |
Hezhe Qiao; Guansong Pang; | nips | 2023-10-24 |
| 80 | Real3D-AD: A Dataset of Point Cloud Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Additionally, we present a comprehensive benchmark for Real3D-AD, revealing the absence of baseline methods for high-precision point cloud anomaly detection. To address this, we propose Reg3D-AD, a registration-based 3D anomaly detection method incorporating a novel feature memory bank that preserves local and global representations. |
JIAQI LIU et. al. | nips | 2023-10-24 |
| 81 | Nominality Score Conditioned Time Series Anomaly Detection By Point/Sequential Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a framework for unsupervised time series anomaly detection that utilizes point-based and sequence-based reconstruction models. |
Chih-Yu (Andrew) Lai; Fan-Keng Sun; Zhengqi Gao; Jeffrey H Lang; Duane Boning; | nips | 2023-10-24 |
| 82 | GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In response, we present GADBench—a comprehensive benchmark for supervised anomalous node detection on static graphs. |
Jianheng Tang; Fengrui Hua; Ziqi Gao; Peilin Zhao; Jia Li; | nips | 2023-10-24 |
| 83 | Robust Outlier Detection Method Based on Local Entropy and Global Density Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, a few K-nearest-neighbor-based anomaly-detection methods exhibit excellent performance on many datasets, but their sensitivity to the value of K is a critical issue that needs to be addressed. To address these challenges, we propose a novel robust anomaly detection method, called Entropy Density Ratio Outlier Detection (EDROD). |
Kaituo Zhang; Wei Huang; Bingyang Zhang; Jinshan Xu; Xuhua Yang; | arxiv-cs.IT | 2023-10-23 |
| 84 | Nominality Score Conditioned Time Series Anomaly Detection By Point/Sequential Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a framework for unsupervised time series anomaly detection that utilizes point-based and sequence-based reconstruction models. |
Chih-Yu Lai; Fan-Keng Sun; Zhengqi Gao; Jeffrey H. Lang; Duane S. Boning; | arxiv-cs.LG | 2023-10-23 |
| 85 | Concept-based Anomaly Detection in Retail Stores for Automatic Correction Using Mobile Robots Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Co-AD has a peak success rate of 89.90% on anomaly detection image sets of retail objects drawn from the RP2K dataset, compared to 80.81% on the best-performing baseline of a standard ViT auto-encoder. To demonstrate its utility, we describe a robotic mobile manipulation pipeline to autonomously correct the anomalies flagged by Co-AD. |
ADITYA KAPOOR et. al. | arxiv-cs.RO | 2023-10-21 |
| 86 | A Substation Anomaly Detection Method Based on Improved Siamese Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An urgent problem in the process of substation anomaly detection is the scantiness of abnormal substation equipment samples. Conventional anomaly detection methods which use … |
KE CAO et. al. | Other Conferences | 2023-10-19 |
| 87 | Anomaly Detection of Command Shell Sessions Based on DistilBERT: Unsupervised and Supervised Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we implement a comprehensive approach to detect anomalies in Unix shell sessions using a pretrained DistilBERT model, leveraging both unsupervised and supervised learning techniques to identify anomalous activity while minimizing data labeling. |
Zefang Liu; John Buford; | arxiv-cs.CL | 2023-10-19 |
| 88 | Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these methods treat the anomaly examples as from a homogeneous distribution, rendering them less effective in generalizing to unseen anomalies that can be drawn from any distribution. In this paper, we propose to learn heterogeneous anomaly distributions using the limited anomaly examples to address this issue. |
Jiawen Zhu; Choubo Ding; Yu Tian; Guansong Pang; | arxiv-cs.CV | 2023-10-19 |
| 89 | Open-Set Multivariate Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper is the first attempt in providing a novel approach for the open-set TSAD problem, in which a small number of labeled anomalies from a limited class of anomalies are visible in the training phase, with the objective of detecting both seen and unseen anomaly classes in the test phase. |
Thomas Lai; Thi Kieu Khanh Ho; Narges Armanfard; | arxiv-cs.LG | 2023-10-18 |
| 90 | TCF-Trans: Temporal Context Fusion Transformer for Anomaly Detection in Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, a novel temporal context fusion framework: Temporal Context Fusion Transformer (TCF-Trans), is proposed for anomaly detection tasks with applications to time series. |
XINGGAN PENG et. al. | Sensors (Basel, Switzerland) | 2023-10-17 |
| 91 | Data Anomaly Detection for Structural Health Monitoring Based on A Convolutional Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: An overall accuracy of 97.6% was achieved by balancing the database using data augmentation to enlarge the dataset, as shown in the research. |
Soon-Young Kim; Mukhriddin Mukhiddinov; | Sensors (Basel, Switzerland) | 2023-10-17 |
| 92 | Research on SDN Traffic Anomaly Detection Technology Based on Knowledge Graph Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: SDN (Software Defined Networking) is a novel network architecture that allows for flexible configuration and centralized control of resources. However, it also presents new fault … |
Suyang Li; Xiaojun Bai; Shenhang Wang; | International Conference on Artificial Intelligence and … | 2023-10-16 |
| 93 | Model Selection of Anomaly Detectors in The Absence of Labeled Validation Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a general-purpose framework for evaluating image-based anomaly detectors with synthetically generated validation data. |
Clement Fung; Chen Qiu; Aodong Li; Maja Rudolph; | arxiv-cs.LG | 2023-10-16 |
| 94 | DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, due to the rapid increase in data scale and dimensionality, the issues of noise and Weak Identity Mapping (WIM) during time series reconstruction have become increasingly pronounced. To address this, we introduce a novel Adaptive Dynamic Neighbor Mask (ADNM) mechanism and integrate it with the Transformer and Denoising Diffusion Model, creating a new framework for multivariate time series anomaly detection, named Denoising Diffusion Mask Transformer (DDMT). |
Chaocheng Yang; Tingyin Wang; Xuanhui Yan; | arxiv-cs.LG | 2023-10-12 |
| 95 | A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes Via Deviation Relationship Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the current anomaly detectors are limited to a single modality and single scene, since they aim to learn the varying background distribution. Motivated by the universal anomaly deviation pattern, in that anomalies exhibit deviations from their local context, we exploit this characteristic to build a unified anomaly detector. |
Jingtao Li; Xinyu Wang; Hengwei Zhao; Liangpei Zhang; Yanfei Zhong; | arxiv-cs.CV | 2023-10-11 |
| 96 | Food Adulteration Identification Framework Via Unsupervised Anomaly Detection Algorithm: Applied to Camel Milk (FIAD） Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Food adulteration driven by economic interests is an important cause of food safety. Camel milk is widely sought for its high nutritional and medicinal value; some businesses … |
YILIN LI et. al. | Conference on Advanced Algorithms and Signal Image … | 2023-10-10 |
| 97 | Equipment Anomaly Detection Method Under Cloud-edge Collaboration Model Based Bi-directional Long Short-term Memory and Variational Autoencoder Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming at the problems of large amount of heterogeneous Industrial data, high fault concealment, complex feature engineering of traditional methods, an anomaly detection method … |
Chao Yin; Yujie Liu; Xiaobin Li; | Conference on Advanced Algorithms and Signal Image … | 2023-10-10 |
| 98 | Anomaly Detection Method of Power Purchase Material Data Based on BIRCH Clustering Algorithm and Time Series Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: At present, the conventional detection methods for abnormal data of power purchase materials mainly use correlation vector machines to extract and reduce the dimensions of data … |
Ning Guo; Pengju Wang; | Conference on Advanced Algorithms and Signal Image … | 2023-10-10 |
| 99 | AnoDODE: Anomaly Detection with Diffusion ODE Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: More precisely, we propose a new anomaly detection method based on diffusion ODEs by estimating the density of features extracted from multi-scale medical images. |
Xianyao Hu; Congming Jin; | arxiv-cs.CV | 2023-10-10 |
| 100 | Assessing The Impact of A Supervised Classification Filter on Flow-based Hybrid Network Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper aims to measure the impact of a supervised filter (classifier) in network anomaly detection. |
Dominik Macko; Patrik Goldschmidt; Peter Pištek; Daniela Chudá; | arxiv-cs.AI | 2023-10-10 |
| 101 | Quantum Support Vector Data Description for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce quantum support vector data description (QSVDD), an unsupervised learning algorithm designed for anomaly detection. |
Hyeondo Oh; Daniel K. Park; | arxiv-quant-ph | 2023-10-10 |
| 102 | MFAD: A Graph Anomaly Detection Framework Based on Multi-frequency Reconstruction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Graph anomaly detection in graph data has received significant attention due to its practical significance in various vital applications such as network security, finance, and … |
SENBAO HOU et. al. | Conference on Advanced Algorithms and Signal Image … | 2023-10-10 |
| 103 | Full Phase Space Resonant Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a proof of principle, we show that the signal from the R\&D dataset from the LHC Olympics is findable with this method, opening up the door to future studies that explore the interplay between depth and breadth in the representation of the data for anomaly detection. |
ERIK BUHMANN et. al. | arxiv-hep-ph | 2023-10-10 |
| 104 | A Supervised Embedding and Clustering Anomaly Detection Method for Classification of Mobile Network Faults Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper introduces Supervised Embedding and Clustering Anomaly Detection (SEMC-AD), a method designed to efficiently identify faulty alarm logs in a mobile network and alleviate the challenges of manual monitoring caused by the growing volume of alarm logs. |
R. Mosayebi; H. Kia; A. Kianpour Raki; | arxiv-cs.LG | 2023-10-10 |
| 105 | LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose a Light and Anti-overfitting Retraining Approach (LARA) for deep variational auto-encoder based time series anomaly detection methods (VAEs). |
FEIYI CHEN et. al. | arxiv-cs.LG | 2023-10-09 |
| 106 | Knowledge Distillation for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel procedure based on knowledge distillation for compressing an unsupervised anomaly detection model into a supervised deployable one and we suggest a set of techniques to improve the detection sensitivity. |
ADRIAN ALAN POL et. al. | arxiv-cs.LG | 2023-10-09 |
| 107 | Successive Data Injection in Conditional Quantum GAN Applied to Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: When detecting anomalies in time series using QGANs, huge challenges arise due to the limited number of qubits compared to the size of the data. To address these challenges, we propose a new high-dimensional encoding approach, named Successive Data Injection (SuDaI). |
Benjamin Kalfon; Soumaya Cherkaoui; Jean-Frédéric Laprade; Ola Ahmad; Shengrui Wang; | arxiv-cs.LG | 2023-10-08 |
| 108 | A Lightweight Video Anomaly Detection Model with Weak Supervision and Adaptive Instance Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we develop a lightweight video anomaly detection model. |
Yang Wang; Jiaogen Zhou; Jihong Guan; | arxiv-cs.CV | 2023-10-08 |
| 109 | Anomaly Detection in A Smart Industrial Machinery Plant Using IoT and Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In an increasingly technology-driven world, the security of Internet-of-Things systems has become a top priority. This article presents a study on the implementation of security … |
Angel Jaramillo-Alcazar; Jaime Govea; William Villegas-Ch; | Sensors (Basel, Switzerland) | 2023-10-07 |
| 110 | Privacy-Preserving Financial Anomaly Detection Via Federated Learning & Multi-Party Computation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we describe a privacy-preserving framework that allows FIs to jointly train highly accurate anomaly detection models. |
SUNPREET ARORA et. al. | arxiv-cs.CR | 2023-10-06 |
| 111 | Improving Vision Anomaly Detection with The Guidance of Language Modality Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we propose Cross-modal Guidance (CMG), which consists of Cross-modal Entropy Reduction (CMER) and Cross-modal Linear Embedding (CMLE), to tackle the redundant information issue and sparse space issue, respectively. |
Dong Chen; Kaihang Pan; Guoming Wang; Yueting Zhuang; Siliang Tang; | arxiv-cs.CV | 2023-10-04 |
| 112 | A Prototype-Based Neural Network for Image Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes ProtoAD, a prototype-based neural network for image anomaly detection and localization. |
Chao Huang; Zhao Kang; Hong Wu; | arxiv-cs.CV | 2023-10-04 |
| 113 | Hyperspectral Anomaly Detection Via Spectral Difference Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Hyperspectral anomaly detection is an active topic in remote sensing application research. Researchers have proposed many detection methods based on spatial differences to detect … |
Zhuang Li; Ye Zhang; | Optical Engineering + Applications | 2023-10-04 |
| 114 | Delving Into CLIP Latent Space for Video Anomaly Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We tackle the complex problem of detecting and recognising anomalies in surveillance videos at the frame level, utilising only video-level supervision. |
LUCA ZANELLA et. al. | arxiv-cs.CV | 2023-10-04 |
| 115 | Beyond The Benchmark: Detecting Diverse Anomalies in Videos Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this research, we advocate for an expansion of VAD investigations to encompass intricate anomalies that extend beyond conventional benchmark boundaries. |
Yoav Arad; Michael Werman; | arxiv-cs.CV | 2023-10-03 |
| 116 | Self-supervised Learning for Anomaly Detection in Computational Workflows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although the use of graph neural networks can help capture complex inter-dependencies, the scarcity of labeled anomalous examples from workflow executions is still a significant challenge. To address this problem, we introduce an autoencoder-driven self-supervised learning~(SSL) approach that learns a summary statistic from unlabeled workflow data and estimates the normal behavior of the computational workflow in the latent space. |
HONGWEI JIN et. al. | arxiv-cs.LG | 2023-10-02 |
| 117 | Counterfactual Graph Learning for Anomaly Detection on Attributed Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Graph anomaly detection is attracting remarkable multidisciplinary research interests ranging from finance, healthcare, and social network analysis. Recent advances on graph … |
CHUNJING XIAO et. al. | IEEE Transactions on Knowledge and Data Engineering | 2023-10-01 |
| 118 | Active Anomaly Detection in Confined Spaces Using Ergodic Traversal of Directed Region Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We provide the first step toward developing a hierarchical control-estimation framework to actively plan robot trajectories for anomaly detection in confined spaces. |
Benjamin Wong; Tyler M. Paine; Santosh Devasia; Ashis G. Banerjee; | arxiv-cs.RO | 2023-10-01 |
| 119 | Going Beyond Familiar Features for Deep Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel approach to AD using explainability to capture novel features as unexplained observations in the input space. |
Sarath Sivaprasad; Mario Fritz; | arxiv-cs.LG | 2023-10-01 |
| 120 | Deep Attention SMOTE: Data Augmentation with A Learnable Interpolation Factor for Imbalanced Anomaly Detection of Gas Turbines Related Papers Related Patents Related Grants Related Venues Related Experts View |
DAN LIU et. al. | Comput. Ind. | 2023-10-01 |
| 121 | Anomaly Detection in Power Generation Plants with Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores the use of Generative Adversarial Networks (GANs) for anomaly detection in power generation plants. |
Marcellin Atemkeng; Toheeb Aduramomi Jimoh; | arxiv-cs.LG | 2023-09-30 |
| 122 | Unravel Anomalies: An End-to-end Seasonal-Trend Decomposition Approach for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce TADNet, an end-to-end TAD model that leverages Seasonal-Trend Decomposition to link various types of anomalies to specific decomposition components, thereby simplifying the analysis of complex time-series and enhancing detection performance. |
Zhenwei Zhang; Ruiqi Wang; Ran Ding; Yuantao Gu; | arxiv-cs.LG | 2023-09-30 |
| 123 | Probabilistic Sampling-Enhanced Temporal-Spatial GCN: A Scalable Framework for Transaction Anomaly Detection in Ethereum Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While Graph Neural Networks (GNNs) have pioneered anomaly detection in such platforms, capturing the intricacies of both spatial and temporal transactional patterns has remained a challenge. This study presents a fusion of Graph Convolutional Networks (GCNs) with Temporal Random Walks (TRW) enhanced by probabilistic sampling to bridge this gap. |
Stefan Kambiz Behfar; Jon Crowcroft; | arxiv-cs.LG | 2023-09-29 |
| 124 | Data-Driven Network Analysis for Anomaly Traffic Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cybersecurity is a critical issue in today’s internet world. Classical security systems, such as firewalls based on signature detection, cannot detect today’s sophisticated … |
Shumon Alam; Yasin Alam; Suxia Cui; Cajetan Akujuobi; | Sensors (Basel, Switzerland) | 2023-09-29 |
| 125 | An Attentional Recurrent Neural Network for Occlusion-Aware Proactive Anomaly Detection in Field Robot Navigation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present an attention-based recurrent neural network architecture for proactive anomaly detection that fuses current sensory inputs and planned control actions with a latent representation of prior robot state. |
Andre Schreiber; Tianchen Ji; D. Livingston McPherson; Katherine Driggs-Campbell; | arxiv-cs.RO | 2023-09-28 |
| 126 | Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose an Anomalous Attention mechanism for weakly-supervised anomaly detection to tackle the aforementioned problems. |
Yidan Fan; Yongxin Yu; Wenhuan Lu; Yahong Han; | arxiv-cs.CV | 2023-09-28 |
| 127 | Algorithmic Recourse for Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on algorithmic recourse in time series anomaly detection, which is to recommend fixing actions on abnormal time series with a minimum cost so that domain experts can understand how to fix the abnormal behavior. |
Xiao Han; Lu Zhang; Yongkai Wu; Shuhan Yuan; | arxiv-cs.LG | 2023-09-28 |
| 128 | Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are three major challenges to the practical application of this approach: 1) the reconstruction quality needs to be further improved since it has a great impact on the final result, especially for images with structural changes; 2) it is observed that for many neural networks, the anomalies can also be well reconstructed, which severely violates the underlying assumption; 3) since reconstruction is an ill-conditioned problem, a test instance may correspond to multiple normal patterns, but most current reconstruction-based methods have ignored this critical fact. In this paper, we propose DiffAD, a method for unsupervised anomaly detection based on the latent diffusion model, inspired by its ability to generate high-quality and diverse images. |
XINYI ZHANG et. al. | iccv | 2023-09-27 |
| 129 | Normalizing Flows for Human Pose Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our model works directly on human pose graph sequences and is exceptionally lightweight ( 1K parameters), capable of running on any machine able to run the pose estimation with negligible additional resources. We leverage the highly compact pose representation in a normalizing flows framework, which we extend to tackle the unique characteristics of spatio-temporal pose data and show its advantages in this use case. |
Or Hirschorn; Shai Avidan; | iccv | 2023-09-27 |
| 130 | Remembering Normality: Memory-guided Knowledge Distillation for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Trained on anomaly-free data, the student still well reconstructs anomalous representations for anomalies and is sensitive to fine patterns in normal data, which also appear in training. To mitigate this issue, we introduce a novel Memory-guided Knowledge-Distillation (MemKD) framework that adaptively modulates the normality of student features in detecting anomalies. |
ZHIHAO GU et. al. | iccv | 2023-09-27 |
| 131 | PNI : Industrial Anomaly Detection Using Position and Neighborhood Information Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these methods neglect the impact of position and neighborhood information on the distribution of normal features. To overcome this, we propose a new algorithm, PNI, which estimates the normal distribution using conditional probability given neighborhood features, modeled with a multi-layer perceptron network. |
Jaehyeok Bae; Jae-Han Lee; Seyun Kim; | iccv | 2023-09-27 |
| 132 | TeD-SPAD: Temporal Distinctiveness for Self-Supervised Privacy-Preservation for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose TeD-SPAD, a privacy-aware video anomaly detection framework that destroys visual private information in a self-supervised manner. |
Joseph Fioresi; Ishan Rajendrakumar Dave; Mubarak Shah; | iccv | 2023-09-27 |
| 133 | Feature Prediction Diffusion Model for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by the impressive generative and anti-noise capacity of diffusion model (DM), in this work, we introduce a novel DM-based method to predict the features of video frames for anomaly detection. |
Cheng Yan; Shiyu Zhang; Yang Liu; Guansong Pang; Wenjun Wang; | iccv | 2023-09-27 |
| 134 | Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In our previous work, we proposed a digital twin-based anomaly detection method, called ATTAIN, which takes advantage of both historical and real-time data of CPS. |
Qinghua Xu; Shaukat Ali; Tao Yue; | arxiv-cs.LG | 2023-09-27 |
| 135 | Removing Anomalies As Noises for Industrial Defect Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a denoising model to detect and localize the anomalies with a generative diffusion model. |
Fanbin Lu; Xufeng Yao; Chi-Wing Fu; Jiaya Jia; | iccv | 2023-09-27 |
| 136 | Anomaly Detection Using Score-based Perturbation Resilience Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel unsupervised anomaly detection method leveraging the score-based model. |
Woosang Shin; Jonghyeon Lee; Taehan Lee; Sangmoon Lee; Jong Pil Yun; | iccv | 2023-09-27 |
| 137 | Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal. |
ALESSANDRO FLABOREA et. al. | iccv | 2023-09-27 |
| 138 | FastRecon: Few-shot Industrial Anomaly Detection Via Fast Feature Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a few-shot anomaly detection strategy that works in a low-data regime and can generalize across products at no cost. |
ZHENG FANG et. al. | iccv | 2023-09-27 |
| 139 | Anomaly Detection Under Distribution Shift Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we consider the problem of anomaly detection under distribution shift and establish performance benchmarks on four widely-used AD and out-of-distribution (OOD) generalization datasets. |
Tri Cao; Jiawen Zhu; Guansong Pang; | iccv | 2023-09-27 |
| 140 | Unsupervised Anomaly Detection By Densely Contrastive Learning for Time Series Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Time series data continuously collected by different sensors play an essential role in monitoring and predicting events in many real-world applications, and anomaly detection for … |
Wei Zhu; Weijian Li; E Ray Dorsey; Jiebo Luo; | Neural networks : the official journal of the International … | 2023-09-26 |
| 141 | SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a Self-supervised Anomaly Detection technique, called SeMAnD, to detect geometric anomalies in Multimodal geospatial datasets. |
Daria Reshetova; Swetava Ganguli; C. V. Krishnakumar Iyer; Vipul Pandey; | arxiv-cs.AI | 2023-09-26 |
| 142 | LogGPT: Log Anomaly Detection Via GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To fill up the gap, we propose LogGPT, a novel framework that employs GPT for log anomaly detection. |
Xiao Han; Shuhan Yuan; Mohamed Trabelsi; | arxiv-cs.LG | 2023-09-25 |
| 143 | FDEPCA: A Novel Adaptive Nonlinear Feature Extraction Method Via Fruit Fly Olfactory Neural Network for IoMT Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proposed method overcomes the problems of present nonlinear feature extraction in the face of high-dimensional outliers where the intrinsic geometric structure of the data is severely distorted and computationally expensive. |
YIHAN CHEN et. al. | IEEE journal of biomedical and health informatics | 2023-09-25 |
| 144 | Divide and Conquer in Video Anomaly Detection: A Comprehensive Review and New Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: It’s noteworthy that recent methods in video anomaly detection have revealed the application of the divide and conquer philosophy (albeit with distinct perspectives from traditional usage), yielding impressive outcomes. This paper systematically reviews these literatures from six dimensions, aiming to enhance the use of the divide and conquer strategy in video anomaly detection. |
Jian Xiao; Tianyuan Liu; Genlin Ji; | arxiv-cs.CV | 2023-09-25 |
| 145 | Semi-Supervised Anomaly Detection of Dissolved Oxygen Sensor in Wastewater Treatment Plants Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As the world progresses toward a digitally connected and sustainable future, the integration of semi-supervised anomaly detection in wastewater treatment processes (WWTPs) … |
Liliana Maria Ghinea; Mihaela Miron; Marian Barbu; | Sensors (Basel, Switzerland) | 2023-09-22 |
| 146 | Using An Anomaly Detection Approach for The Segmentation of Colorectal Cancer Tumors in Whole Slide Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Colorectal cancer (CRC) is the second most commonly diagnosed cancer in the United States. Genetic testing is critical in assisting in the early detection of CRC and selection of … |
QIANGQIANG GU et. al. | Journal of pathology informatics | 2023-09-22 |
| 147 | Back To The Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that using boosted decision trees as classifiers in weakly supervised anomaly detection gives superior performance compared to deep neural networks. |
THORBEN FINKE et. al. | arxiv-hep-ph | 2023-09-22 |
| 148 | Combining Resonant and Tail-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that CATHODE, despite being model-agnostic, is nevertheless competitive with dedicated cut-based searches, while simultaneously covering a much wider region of parameter space. |
Gerrit Bickendorf; Manuel Drees; Gregor Kasieczka; Claudius Krause; David Shih; | arxiv-hep-ph | 2023-09-22 |
| 149 | Ano-SuPs: Multi-size Anomaly Detection for Manufactured Products By Identifying Suspected Patches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, the uncertainty of the anomaly can cause anomaly contamination problems, making the designed model and method highly susceptible to external disturbances. To address these challenges, we propose a two-stage strategy anomaly detection method that detects anomalies by identifying suspected patches (Ano-SuPs). |
Hao Xu; Juan Du; Andi Wang; | arxiv-stat.ML | 2023-09-20 |
| 150 | Autoencoder-based Anomaly Detection System for Online Data Quality Monitoring of The CMS Electromagnetic Calorimeter Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. |
The CMS ECAL Collaboration; | arxiv-physics.ins-det | 2023-09-18 |
| 151 | An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thereby, the gap between the assumption and actual training data affects detrimentally in learning of an anomaly detection model. In this work, we propose a learning framework to reduce this gap and achieve better normality representation. |
Minkyung Kim; Jongmin Yu; Junsik Kim; Tae-Hyun Oh; Jun Kyun Choi; | arxiv-cs.LG | 2023-09-17 |
| 152 | Active Anomaly Detection Based on Deep One-class Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle two essential problems of active learning for Deep SVDD: query strategy and semi-supervised learning method. |
Minkyung Kim; Junsik Kim; Jongmin Yu; Jun Kyun Choi; | arxiv-cs.LG | 2023-09-17 |
| 153 | Understanding The Limitations of Self-supervised Learning for Tabular Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the limitations of self-supervision for tabular anomaly detection. |
Kimberly T. Mai; Toby Davies; Lewis D. Griffin; | arxiv-cs.LG | 2023-09-15 |
| 154 | FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing models usually suffer from the trade-off between normal reconstruction fidelity and abnormal reconstruction distinguishability, which damages the performance. In this paper, we find that the above trade-off can be better mitigated by leveraging the distinct frequency biases between normal and abnormal reconstruction errors. |
TONGKUN LIU et. al. | arxiv-cs.CV | 2023-09-13 |
| 155 | GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Understanding these relations is vital for detecting anomalies and their underlying causes. To address this issue, we introduce GLAD, a Graph-based Log Anomaly Detection framework designed to detect relational anomalies in system logs. |
YUFEI LI et. al. | arxiv-cs.LG | 2023-09-12 |
| 156 | Interactive Learning for Network Anomaly Monitoring and Detection with Human Guidance in The Loop Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the advancement in big data and cloud computing technology, we have witnessed tremendous developments in applying intelligent techniques in network operation and management. … |
Dong Yang; Ze Liu; Songjie Wei; | Sensors (Basel, Switzerland) | 2023-09-11 |
| 157 | Effective Abnormal Activity Detection on Multivariate Time Series Healthcare Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Consequently, achieving accurate anomaly detection is challenging since we have to capture both temporal dependencies of time series and inter-relationships among variables. To address this problem, we propose a Residual-based Anomaly Detection approach, Rs-AD, for effective representation learning and abnormal activity detection. |
Mengjia Niu; Yuchen Zhao; Hamed Haddadi; | arxiv-cs.LG | 2023-09-11 |
| 158 | Research on Key Technologies of Space-based Surface Anomaly Instant Detection System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The existing space-based remote sensing has problems such as weak collaboration, slow response, and long links, which cannot meet the application requirements of real-time anomaly … |
HAN GAO et. al. | Conference on Computer Science and Communication Technology | 2023-09-11 |
| 159 | Self-Supervised Multi-Scale Cropping and Simple Masked Attentive Predicting for Lung CT-Scan Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a self-supervised framework for learning representations of lung CT-scan images via both multi-scale cropping and simple masked attentive predicting, which is capable of constructing a powerful out-of-distribution detector. |
Wei Li; Guanghai Liu; Haoyi Fan; Zuoyong Li; David Zhang; | IEEE transactions on medical imaging | 2023-09-11 |
| 160 | The Role of Noise in Denoising Models for Anomaly Detection in Medical Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Pathological brain lesions exhibit diverse appearance in brain images, in terms of intensity, texture, shape, size, and location. Comprehensive sets of data and annotations are … |
ANTANAS KASCENAS et. al. | Medical image analysis | 2023-09-11 |
| 161 | Knowledge Distillation-Empowered Digital Twin for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, in this paper, we propose a novel method named KDDT for TCMS anomaly detection. |
Qinghua Xu; Shaukat Ali; Tao Yue; Zaimovic Nedim; Inderjeet Singh; | arxiv-cs.LG | 2023-09-08 |
| 162 | Curved Geometric Networks for Visual Anomaly Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the benefits of the curved space for analyzing anomalous, open-set, or out-of-distribution (OOD) objects in data. |
JIE HONG et. al. | IEEE transactions on neural networks and learning systems | 2023-09-08 |
| 163 | Evaluation of The Application of Sequence Data to The Identification of Outbreaks of Disease Using Anomaly Detection Methods Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection methods have a great potential to assist the detection of diseases in animal production systems. We used sequence data of Porcine Reproductive and Respiratory … |
José Manuel Díaz-Cao; Xin Liu; Jeonghoon Kim; Maria Jose Clavijo; Beatriz Martínez-López; | Veterinary research | 2023-09-08 |
| 164 | A Method for Detecting Abnormal Behavior of Ships Based on Multi-dimensional Density Distance and An Abnormal Isolation Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposed an abnormal ship behavior detection method based on distance measurement and an isolation mechanism. |
Lixiang Zhang; Yian Zhu; Jie Ren; Wei Lu; Ye Yao; | Mathematical biosciences and engineering : MBE | 2023-09-07 |
| 165 | Alert Classification for The ALeRCE Broker System: The Anomaly Detector Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Astronomical broker systems, such as Automatic Learning for the Rapid Classification of Events (ALeRCE), are currently analyzing hundreds of thousands of alerts per night, opening … |
M. PÉREZ-CARRASCO et. al. | The Astronomical Journal | 2023-09-07 |
| 166 | A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Several publicly available data sets, such as HDFS, BGL, Thunderbird, OpenStack, and Hadoop, have since become standards for evaluating these anomaly detection techniques, however, the appropriateness of these data sets has not been closely investigated in the past. In this paper we therefore analyze six publicly available log data sets with focus on the manifestations of anomalies and simple techniques for their detection. |
Max Landauer; Florian Skopik; Markus Wurzenberger; | arxiv-cs.LG | 2023-09-06 |
| 167 | Reasonable Anomaly Detection in Long Sequences Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to completely represent the motion patterns of objects by learning from long-term sequences. |
Yalong Jiang; Changkang Li; | arxiv-cs.CV | 2023-09-06 |
| 168 | Resilient VAE: Unsupervised Anomaly Detection at The SLAC Linac Coherent Light Source Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces the Resilient Variational Autoencoder (ResVAE), a deep generative model specifically designed for anomaly detection. |
Ryan Humble; William Colocho; Finn O’Shea; Daniel Ratner; Eric Darve; | arxiv-physics.acc-ph | 2023-09-05 |
| 169 | Anomaly Detection with Semi-supervised Classification Based on Risk Estimators Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A significant limitation of one-class classification anomaly detection methods is their reliance on the assumption that unlabeled training data only contains normal instances. To overcome this impractical assumption, we propose two novel classification-based anomaly detection methods. |
Le Thi Khanh Hien; Sukanya Patra; Souhaib Ben Taieb; | arxiv-cs.LG | 2023-09-01 |
| 170 | MUD Enabled Deep Learning Framework for Anomaly Detection in IoT Integrated Smart Building Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mirdula S; R. M; | e-Prime – Advances in Electrical Engineering, Electronics … | 2023-09-01 |
| 171 | Robust Anomaly Detection for Multivariate Time Series Through Temporal GCNs and Attention-based VAE Related Papers Related Patents Related Grants Related Venues Related Experts View |
YUNFEI SHI et. al. | Knowl. Based Syst. | 2023-09-01 |
| 172 | Masked Graph Neural Networks for Unsupervised Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new method-masked graph neural networks for unsupervised anomaly detection (MGUAD). |
KANG XU et. al. | Sensors (Basel, Switzerland) | 2023-08-31 |
| 173 | Deep Semi-Supervised Anomaly Detection for Finding Fraud in The Futures Market Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research article aims to evaluate the efficacy of a deep semi-supervised anomaly detection technique, called Deep SAD, for detecting fraud in high-frequency financial data. |
Timothy DeLise; | arxiv-cs.LG | 2023-08-31 |
| 174 | Classification of Anomalies in Telecommunication Network KPI Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the classification of anomalies detected on network Key Performance Indicators (KPI) has received less attention, resulting in a lack of information about anomaly characteristics and classification processes. To address this gap, this paper proposes a modular anomaly classification framework. |
Korantin Bordeau-Aubert; Justin Whatley; Sylvain Nadeau; Tristan Glatard; Brigitte Jaumard; | arxiv-cs.LG | 2023-08-30 |
| 175 | Demo: A Digital Twin of The 5G Radio Access Network for Anomaly Detection Functionality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recently, the concept of digital twins (DTs) has received significant attention within the realm of 5G/6G. This demonstration shows an innovative DT design and implementation framework tailored toward integration within the 5G infrastructure. |
Peizheng Li; Adnan Aijaz; Tim Farnham; Sajida Gufran; Sita Chintalapati; | arxiv-cs.NI | 2023-08-30 |
| 176 | MadSGM: Multivariate Anomaly Detection with Score-based Generative Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we present a multivariate time-series anomaly detector based on score-based generative models, called MadSGM, which considers the broadest ever set of anomaly measurement factors: i) reconstruction-based, ii) density-based, and iii) gradient-based anomaly measurements. |
HAKSOO LIM et. al. | arxiv-cs.LG | 2023-08-29 |
| 177 | A Comprehensive Augmentation Framework for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Data augmentation methods are commonly integrated into the training of anomaly detection models. Previous approaches have primarily focused on replicating real-world anomalies or enhancing diversity, without considering that the standard of anomaly varies across different classes, potentially leading to a biased training distribution.This paper analyzes crucial traits of simulated anomalies that contribute to the training of reconstructive networks and condenses them into several methods, thus creating a comprehensive framework by selectively utilizing appropriate combinations.Furthermore, we integrate this framework with a reconstruction-based approach and concurrently propose a split training strategy that alleviates the issue of overfitting while avoiding introducing interference to the reconstruction process. |
Jiang Lin; Yaping Yan; | arxiv-cs.AI | 2023-08-29 |
| 178 | ADFA: Attention-augmented Differentiable Top-k Feature Adaptation for Unsupervised Medical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The scarcity of annotated data, particularly for rare diseases, limits the variability of training data and the range of detectable lesions, presenting a significant challenge for supervised anomaly detection in medical imaging. To solve this problem, we propose a novel unsupervised method for medical image anomaly detection: Attention-Augmented Differentiable top-k Feature Adaptation (ADFA). |
Yiming Huang; Guole Liu; Yaoru Luo; Ge Yang; | arxiv-cs.CV | 2023-08-29 |
| 179 | MSFlow: Multi-Scale Flow-based Framework for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To generalize the anomaly size variation, we propose a novel Multi-Scale Flow-based framework dubbed MSFlow composed of asymmetrical parallel flows followed by a fusion flow to exchange multi-scale perceptions. |
Yixuan Zhou; Xing Xu; Jingkuan Song; Fumin Shen; Heng Tao Shen; | arxiv-cs.CV | 2023-08-29 |
| 180 | Neural Network Training Strategy to Enhance Anomaly Detection Performance: A Perspective on Reconstruction Loss Amplification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, we note that containing of generalization ability in reconstruction can also be obtained simply from steep-shaped loss landscape. Motivated by this, we propose a loss landscape sharpening method by amplifying the reconstruction loss, dubbed Loss AMPlification (LAMP). |
YEONGHYEON PARK et. al. | arxiv-cs.CV | 2023-08-28 |
| 181 | Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an anomalous sound detection method using self-attention-based frequency pattern analysis and spectral-temporal information fusion. |
Hejing Zhang; Jian Guan; Qiaoxi Zhu; Feiyang Xiao; Youde Liu; | arxiv-cs.SD | 2023-08-27 |
| 182 | Bias in Unsupervised Anomaly Detection in Brain MRI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a novel analysis of biases in unsupervised anomaly detection. |
COSMIN I. BERCEA et. al. | arxiv-eess.IV | 2023-08-26 |
| 183 | Online Video Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the popularity of video surveillance technology, people are paying more and more attention to how to detect abnormal states or events in videos in time. Therefore, real-time, … |
Yuxing Zhang; Jinchen Song; Yuehan Jiang; Hongjun Li; | Sensors (Basel, Switzerland) | 2023-08-26 |
| 184 | Graph Evolution-Based Vertex Extraction for Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we propose a novel approach to hyperspectral anomaly detection that characterizes the HSI data using a vertex-and edge-weighted graph with the pixels as vertices. |
Xianchang Yang; Bing Tu; Qianming Li; Jun Li; Antonio Plaza; | IEEE transactions on neural networks and learning systems | 2023-08-25 |
| 185 | A Generic Machine Learning Framework for Fully-Unsupervised Anomaly Detection with Contaminated Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce a framework for a fully unsupervised refinement of contaminated training data for AD tasks. |
Markus Ulmer; Jannik Zgraggen; Lilach Goren Huber; | arxiv-cs.LG | 2023-08-25 |
| 186 | Try with Simpler — An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This approach aims to extract meaning from log events (log message templates) and develop advanced DL models for anomaly detection. |
LIN YANG et. al. | arxiv-cs.LG | 2023-08-24 |
| 187 | REB: Reducing Biases in Representation for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Reducing Biases (REB) in representation by considering the domain bias of the pre-trained model and building a self-supervised learning task for better domain adaption with a defect generation strategy (DefectMaker) imitating the natural defects. |
Shuai Lyu; Dongmei Mo; Waikeung Wong; | arxiv-cs.CV | 2023-08-24 |
| 188 | Low-count Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Low-count time series describe sparse or intermittent events, which are prevalent in large-scale online platforms that capture and monitor diverse data types. |
Philipp Renz; Kurt Cutajar; Niall Twomey; Gavin K. C. Cheung; Hanting Xie; | arxiv-cs.LG | 2023-08-24 |
| 189 | Multivariate Time-Series Anomaly Detection with Contaminated Data: Application to Physiological Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel and practical end-to-end unsupervised TSAD when the training data are contaminated with anomalies. |
Thi Kieu Khanh Ho; Narges Armanfard; | arxiv-cs.LG | 2023-08-24 |
| 190 | SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present semi-supervised anomaly detection (SAD), an end-to-end framework for anomaly detection on dynamic graphs. |
SHENG TIAN et. al. | ijcai | 2023-08-23 |
| 191 | Beyond Homophily: Robust Graph Anomaly Detection Via Neural Sparsification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose SparseGAD, a novel GAD framework that sparsifies the structures of target graphs to effectively reduce noises and collaboratively learns node representations. |
ZHENG GONG et. al. | ijcai | 2023-08-23 |
| 192 | OptIForest: Optimal Isolation Forest for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we establish a theory on isolation efficiency to answer the question and determine the optimal branching factor for an isolation tree. |
HAOLONG XIANG et. al. | ijcai | 2023-08-23 |
| 193 | Federated Learning for Predictive Maintenance and Anomaly Detection Using Time Series Data Distribution Shifts in Manufacturing Processes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the manufacturing process, equipment failure is directly related to productivity, so predictive maintenance plays a very important role. Industrial parks are distributed, and … |
Jisu Ahn; Younjeong Lee; Namji Kim; Chanho Park; Jongpil Jeong; | Sensors (Basel, Switzerland) | 2023-08-22 |
| 194 | Few-shot Anomaly Detection in Text with Deviation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce FATE, a deep few-shot learning-based framework that leverages limited anomaly examples and learns anomaly scores explicitly in an end-to-end method using deviation learning. |
Anindya Sundar Das; Aravind Ajay; Sriparna Saha; Monowar Bhuyan; | arxiv-cs.LG | 2023-08-22 |
| 195 | VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose VadCLIP, a new paradigm for weakly supervised video anomaly detection (WSVAD) by leveraging the frozen CLIP model directly without any pre-training and fine-tuning process. |
PENG WU et. al. | arxiv-cs.CV | 2023-08-22 |
| 196 | Adaptive Thresholding Heuristic for KPI Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This article proposes an Adaptive Thresholding Heuristic (ATH) to dynamically adjust the detection threshold based on the local properties of the data distribution and adapt to changes in time series patterns. |
Ebenezer R. H. P. Isaac; Akshat Sharma; | arxiv-cs.LG | 2023-08-21 |
| 197 | Random Word Data Augmentation with CLIP for Zero-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel method that leverages a visual-language model, CLIP, as a data source for zero-shot anomaly detection. |
Masato Tamura; | arxiv-cs.CV | 2023-08-21 |
| 198 | Practical Anomaly Detection Over Multivariate Monitoring Metrics for Online Services Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing approaches fall short of industrial needs for being unable to capture such information efficiently. To fill this significant gap, in this paper, we propose CMAnomaly, an anomaly detection framework on multivariate monitoring metrics based on collaborative machine. |
JINYANG LIU et. al. | arxiv-cs.SE | 2023-08-19 |
| 199 | AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Various log-based anomaly detection techniques have been proposed to ensure software reliability. |
YINTONG HUO et. al. | arxiv-cs.SE | 2023-08-18 |
| 200 | CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The normal boundary is often defined tightly, resulting in slight deviations being classified as anomalies, consequently leading to a high false positive rate and a limited ability to generalise normal patterns. To address this, we introduce a novel end-to-end self-supervised ContrAstive Representation Learning approach for time series Anomaly detection (CARLA). |
Zahra Zamanzadeh Darban; Geoffrey I. Webb; Shirui Pan; Charu C. Aggarwal; Mahsa Salehi; | arxiv-cs.LG | 2023-08-18 |
| 201 | Enhancing Anomaly Detection in Distributed Power Systems Using Autoencoder-based Federated Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This centralized approach results in high response time delays and data leakage problems. To address these challenges, we propose an Autoencoder-based Federated Learning method that combines the AutoEncoder and Federated Learning networks to develop a high-accuracy algorithm for identifying anomalies of power consumption data in distributed power systems. |
Kimleang Kea; Youngsun Han; Tae-Kyung Kim; | PloS one | 2023-08-18 |
| 202 | Forensic Data Analytics for Anomaly Detection in Evolving Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This chapter presents a digital analytics framework for network anomaly detection, including multi-perspective feature engineering, unsupervised anomaly detection, and comprehensive result correction procedures. |
LI YANG et. al. | arxiv-cs.CR | 2023-08-17 |
| 203 | Noise-robust Hyperspectral Anomaly Detection Via Relative Total Variation Collaborative Representation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A novel noise-robust hyperspectral anomaly detector based on relative total variation collaborative representation is proposed to settle the problem of low detection probability … |
Chensong Yin; A. Liu; Weitao Sun; Mingjie Wang; Leitao Gao; | International Conference on Laser, Optics and … | 2023-08-17 |
| 204 | Retracted: Adaptive Anomaly Detection Framework Model Objects in Cyberspace Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: [This retracts the article DOI: 10.1155/2020/6660489.]. … |
Applied Bionics And Biomechanics; | Applied bionics and biomechanics | 2023-08-16 |
| 205 | GraphTS: Graph-represented Time Series for Subsequence Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Some methods fail to capture recurrent subsequence anomalies due to using only local or neighborhood information for anomaly detection. To address these limitations, in this paper, we propose a novel graph-represented time series (GraphTS) method for discovering subsequence anomalies. |
Roozbeh Zarei; Guangyan Huang; Junfeng Wu; | PloS one | 2023-08-16 |
| 206 | Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We advocate the application of machine learning (ML) techniques for anomaly (novelty) detection to exoplanet transit spectra, with the goal of identifying planets with unusual chemical composition and even searching for unknown biosignatures. |
Roy T. Forestano; Konstantin T. Matchev; Katia Matcheva; Eyup B. Unlu; | arxiv-astro-ph.EP | 2023-08-15 |
| 207 | Future Video Prediction from A Single Frame for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by the abilities of the future frame prediction proxy-task, we introduce the task of future video prediction from a single frame, as a novel proxy-task for video anomaly detection. |
Mohammad Baradaran; Robert Bergevin; | arxiv-cs.CV | 2023-08-15 |
| 208 | Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes Maat, the first work to address anomaly anticipation of performance metrics in cloud services. |
Cheryl Lee; Tianyi Yang; Zhuangbin Chen; Yuxin Su; Michael R. Lyu; | arxiv-cs.SE | 2023-08-15 |
| 209 | Digital Twin of The Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hereby, technologies envisioned to be integrated in 6G, in particular joint communications and sensing (JCAS) and accurate indoor positioning of transmitters, open up the possibility to build a digital twin (DT) of the radio environment. This paper proposes a new approach for anomaly detection in wireless networks enabled by such a DT which allows to integrate contextual information on the network in the anomaly detection procedure. |
Anton Krause; Mohd Danish Khursheed; Philipp Schulz; Friedrich Burmeister; Gerhard Fettweis; | arxiv-eess.SP | 2023-08-14 |
| 210 | Anomaly Detection of Industrial Motors Under Few-shot Feature Conditions Based on Causality Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It is observed that previous research studies focusing on few-shot feature data for fault diagnosis or anomaly detection have a limitation, that is, feature extraction methods to … |
Yuefeng Cen; Xucheng Li; Gang Cen; Zhigang Cheng; | Measurement Science and Technology | 2023-08-14 |
| 211 | A Method of DDoS Attack Detection and Mitigation for The Comprehensive Coordinated Protection of SDN Controllers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Software defined networking (SDN) improves the flexibility and programmability of the network by separating the control plane and the data plane and effectively realizes the … |
Jin Wang; Liping Wang; Ruiqing Wang; | Entropy (Basel, Switzerland) | 2023-08-14 |
| 212 | A Pre-seismic Anomaly Detection Approach Based on Graph Attention Isomorphism Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Pre-seismic anomaly detection plays a crucial role in reducing economic losses and casualties caused by earthquakes. This paper proposes a novel four-step approach for pre-seismic … |
YONGMING HUANG et. al. | Measurement Science and Technology | 2023-08-14 |
| 213 | ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new GAN model, named Adjusted-LSTM GAN (ALGAN), which adjusts the output of an LSTM network for improved anomaly detection in both univariate and multivariate time series data in an unsupervised setting. |
Md Abul Bashar; Richi Nayak; | arxiv-cs.LG | 2023-08-12 |
| 214 | Exploring The Potential of World Models for Anomaly Detection in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work provides an overview of how world models can be leveraged to perform anomaly detection in the domain of autonomous driving. |
DANIEL BOGDOLL et. al. | arxiv-cs.AI | 2023-08-10 |
| 215 | Deep Spatial-constraints Networks for Unsupervised Anomaly Detection in Multivariate Time Series Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: High-dimensional time series anomaly detection has always been an important challenge in the field of system security. Most existing methods are dedicated to modelling the … |
Yanwen Wu; Di Ge; Y. Cheng; | 4th International Conference on Information Science, … | 2023-08-10 |
| 216 | Retracted: Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: [This retracts the article DOI: 10.1155/2022/8568917.]. … |
Computational Intelligence And Neuroscience; | Computational intelligence and neuroscience | 2023-08-09 |
| 217 | Multi-Scale Memory Comparison for Zero-/Few-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, complex industrial scenarios often involve multiple objects, presenting a significant challenge. In light of this, we propose a straightforward yet powerful multi-scale memory comparison framework for zero-/few-shot anomaly detection. |
Chaoqin Huang; Aofan Jiang; Ya Zhang; Yanfeng Wang; | arxiv-cs.CV | 2023-08-09 |
| 218 | Retracted: Application of A FL Time Series Building Model in Mobile Network Interaction Anomaly Detection in The Internet of Things Environment Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: [This retracts the article DOI: 10.1155/2022/2760966.]. … |
Computational Intelligence And Neuroscience; | Computational intelligence and neuroscience | 2023-08-09 |
| 219 | Multi-Class Deep SVDD: Anomaly Detection Approach in Astronomy with Distinct Inlier Categories Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Multi-Class Deep Support Vector Data Description (MCDSVDD), an extension of the state-of-the-art anomaly detection algorithm One-Class Deep SVDD, specifically designed to handle different inlier categories with distinct data distributions. |
MANUEL PÉREZ-CARRASCO et. al. | arxiv-cs.LG | 2023-08-09 |
| 220 | Retracted: A Deep Spiking Neural Network Anomaly Detection Method Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: [This retracts the article DOI: 10.1155/2022/6391750.]. … |
Computational Intelligence And Neuroscience; | Computational intelligence and neuroscience | 2023-08-09 |
| 221 | Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel approach to dimensionality reduction for AD using pre-trained convolutional neural network (CNN) that incorporate EfficientNet models. |
Tetiana Gula; João P C Bertoldo; | arxiv-cs.CV | 2023-08-09 |
| 222 | Weakly Supervised Anomaly Detection Coupled with Fourier Transform Infrared (FT-IR) Spectroscopy for The Identification of Non-normal Tissue Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work illustrates how a novel approach using a weakly supervised anomaly detection algorithm paired with IR microscopy can detect non-normal tissue spectra. |
Dougal Ferguson; Alex Henderson; Elizabeth F McInnes; Peter Gardner; | The Analyst | 2023-08-07 |
| 223 | Enhancing Smart Home Security: Anomaly Detection and Face Recognition in Smart Home IoT Devices Using Logit-Boosted CNN Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores the application of deep learning models for anomaly detection and face recognition in IoT devices within the context of smart homes. |
ASIF RAHIM et. al. | Sensors (Basel, Switzerland) | 2023-08-06 |
| 224 | Detection of Anomalies in Multivariate Time Series Using Ensemble Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To further enhance the prediction performance, we propose an ensemble technique that combines multiple base models toward the final decision. |
Anastasios Iliopoulos; John Violos; Christos Diou; Iraklis Varlamis; | arxiv-cs.LG | 2023-08-06 |
| 225 | Anomaly Detection in Global Financial Markets with Graph Neural Networks and Nonextensive Entropy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigated the ability to detect anomalies in global financial markets through Graph Neural Networks (GNN) considering an uncertainty scenario measured by a nonextensive entropy. |
Kleyton da Costa; | arxiv-cs.AI | 2023-08-05 |
| 226 | Learning from Positive and Unlabeled Multi-Instance Bags in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite being useful for several use cases, there is no work dedicated to learning from positive and unlabeled data in a multi-instance setting for anomaly detection. Therefore, we propose the first method that learns from PU bags in anomaly detection. |
Lorenzo Perini; Vincent Vercruyssen; Jesse Davis; | kdd | 2023-08-04 |
| 227 | Deep Weakly-supervised Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To detect both seen and unseen anomalies, we introduce a novel deep weakly-supervised approach, namely Pairwise Relation prediction Network (PReNet), that learns pairwise relation features and anomaly scores by predicting the relation of any two randomly sampled training instances, in which the pairwise relation can be anomaly-anomaly, anomaly-unlabeled, or unlabeled-unlabeled. |
Guansong Pang; Chunhua Shen; Huidong Jin; Anton van den Hengel; | kdd | 2023-08-04 |
| 228 | ECGGAN: A Framework for Effective and Interpretable Electrocardiogram Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose ECGGAN, a novel reconstruction-based ECG anomaly detection framework. |
Huazhang Wang; Zhaojing Luo; James W.L. Yip; Chuyang Ye; Meihui Zhang; | kdd | 2023-08-04 |
| 229 | Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing anomaly detection models for time series are primarily trained with normal-point-dominant data and would become ineffective when anomalous points intensively occur in certain episodes. To solve this problem, we propose a new approach, called DiffAD, from the perspective of time series imputation. |
Chunjing Xiao; Zehua Gou; Wenxin Tai; Kunpeng Zhang; Fan Zhou; | kdd | 2023-08-04 |
| 230 | Anomaly Detection with Score Distribution Discrimination Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to optimize the anomaly scoring function from the view of score distribution, thus better retaining the diversity and more fine-grained information of input data, especially when the unlabeled data contains anomaly noises in more practical AD scenarios. |
Minqi Jiang; Songqiao Han; Hailiang Huang; | kdd | 2023-08-04 |
| 231 | Anomaly Detection in Multi-Wavelength Photoplethysmography Using Lightweight Machine Learning Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The main contributions of this paper are proposing a set of features with high information gain for anomaly detection in MW-PPG signals in the classification context, assessing the impact of window size and evaluating various lightweight ML models to achieve highly accurate anomaly detection, and examining the effectiveness of MW-PPG signals in detecting artifacts. |
VLAD-EUSEBIU BACIU et. al. | Sensors (Basel, Switzerland) | 2023-08-04 |
| 232 | Towards Graph-level Anomaly Detection Via Deep Evolutionary Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although deep graph representation learning shows effectiveness in fusing high-level representations and capturing characters of individual graphs, most of the existing works are defective in graph-level anomaly detection because of their limited capability in exploring information across graphs, the imbalanced data distribution of anomalies, and low interpretability of the black-box graph neural networks (GNNs). To overcome these limitations, we propose a novel deep evolutionary graph mapping framework named GmapAD1, which can adaptively map each graph into a new feature space based on its similarity to a set of representative nodes chosen from the graph set. |
Xiaoxiao Ma; Jia Wu; Jian Yang; Quan Z. Sheng; | kdd | 2023-08-04 |
| 233 | Synthetic Outlier Generation for Anomaly Detection in Autonomous Driving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we explore different strategies for training an image semantic segmentation model with an anomaly detection module. |
Martin Bikandi; Gorka Velez; Naiara Aginako; Itziar Irigoien; | arxiv-cs.CV | 2023-08-04 |
| 234 | Achieving State-of-the-art Performance in The Medical Out-of-Distribution (MOOD) Challenge Using Plausible Synthetic Anomalies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study we present a new unsupervised anomaly detection method. |
Sergio Naval Marimont; Giacomo Tarroni; | arxiv-cs.CV | 2023-08-02 |
| 235 | Graph Anomaly Detection at Group Level: A Topology Pattern Enhanced Unsupervised Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing graph anomaly detection algorithms focus on distinguishing individual entities (nodes or graphs) and overlook the possibility of anomalous groups within the graph. To address this limitation, this paper introduces a novel unsupervised framework for a new task called Group-level Graph Anomaly Detection (Gr-GAD). |
XING AI et. al. | arxiv-cs.LG | 2023-08-02 |
| 236 | Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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. | IEEE transactions on image processing : a publication of … | 2023-08-02 |
| 237 | System Health Assessment Model Based on Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Accurately assessing system health and taking timely interventions play a crucial role in promoting intelligent system operation. Traditional system health assessment techniques … |
Hai Yu; Xinyuan Cheng; Juan Liu; Zhengong Cai; Fengmin Lv; | Journal of Physics: Conference Series | 2023-08-01 |
| 238 | A Survey of Time Series Anomaly Detection Methods in The AIOps Domain Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This review offers a comprehensive overview of time series anomaly detection in Artificial Intelligence for IT operations (AIOps), which uses AI capabilities to automate and optimize operational workflows. |
ZHENYU ZHONG et. al. | arxiv-cs.LG | 2023-08-01 |
| 239 | Fabric Defect Detection Using A One-class Classification Based on Depthwise Separable Convolution Autoencoder Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Fabric defect detection is anomaly detection, which is widely studied in the textile industry. Like most anomaly detection tasks, there are some problems hindering detection … |
Chun Chen; X. Deng; Zhuliang Yu; Zhengtao Wu; | Journal of Physics: Conference Series | 2023-08-01 |
| 240 | Anomaly Pixel Detection Via Dual-Branch Uncertainty Metrics Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection aims to detect abnormal samples from normal data. Existing methods mainly use synthesis-based approach and uncertainty-based approach. Moreover, the … |
Peng Luo; Weizhong Guo; | Journal of Physics: Conference Series | 2023-08-01 |
| 241 | Patch-wise Auto-Encoder for Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: On the contrary, we propose a novel patch-wise auto-encoder (Patch AE) framework, which aims at enhancing the reconstruction ability of AE to anomalies instead of weakening it. |
Yajie Cui; Zhaoxiang Liu; Shiguo Lian; | arxiv-cs.CV | 2023-08-01 |
| 242 | An Empirical Study on Log-based Anomaly Detection Using Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive empirical study, in which we evaluate different supervised and semi-supervised, traditional and deep ML techniques w.r.t. four evaluation criteria: detection accuracy, time performance, sensitivity of detection accuracy as well as time performance to hyperparameter tuning. |
SHAN ALI et. al. | arxiv-cs.SE | 2023-07-31 |
| 243 | Using Kernel SHAP XAI Method to Optimize The Network Anomaly Detection Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper aims to detect and explain network anomalies with XAI, kernelSHAP method. |
Khushnaseeb Roshan; Aasim Zafar; | arxiv-cs.LG | 2023-07-31 |
| 244 | General Anomaly Detection of Underwater Gliders Validated By Large-scale Deployment Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper employs an anomaly detection algorithm to assess operational conditions of underwater gliders in the real-world ocean environment. |
Ruochu Yang; Chad Lembke; Fumin Zhang; Catherine Edwards; | arxiv-cs.RO | 2023-07-31 |
| 245 | Anomaly Detection in Annular Metal Turning Surfaces Based on A Priori Information and A Multi-Scale Self-Referencing Template Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To solve the problem of anomaly detection in annular metal turning surfaces, this paper develops an anomaly detection algorithm based on a priori information and a multi-scale … |
Xinyu Suo; Jie Zhang; Jian Liu; Dezhi Yang; Feitao Zhou; | Sensors (Basel, Switzerland) | 2023-07-30 |
| 246 | A Data-driven Approach for Intrusion and Anomaly Detection Using Automated Machine Learning for The Internet of Things IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Hao-Chen Xu; Zihan Sun; Yuan Cao; Hazrat Bilal; | Soft Computing | 2023-07-29 |
| 247 | F-AnoGAN for Non-destructive Testing in Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Being able to identify defects is an essential step during manufacturing processes. Yet, not all defects are necessarily known and sufficiently well described in the databases … |
OUMAIMA SLITI et. al. | International Conference on Quality Control by Artificial … | 2023-07-28 |
| 248 | Frequency Perturbation Analysis for Anomaly Detection Using Fourier Heat Map Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection is an essential task within an industry domain, and sophisticated approaches have been proposed. PaDiM has a promising direction, utilizing ImageNet-pretrained … |
Yoshikazu Hayashi; Hiroaki Aizawa; Shunsuke Nakatsuka; K. Kato; | International Conference on Quality Control by Artificial … | 2023-07-28 |
| 249 | Combining Unsupervised and Supervised Deep Learning Approaches for Surface Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection in an unsupervised manner has become the go-to approach in applications where data labeling proves problematic. However, these approaches aren’t completely … |
Domen Rački; Dejan Tomazevic; D. Skočaj; | International Conference on Quality Control by Artificial … | 2023-07-28 |
| 250 | Anomaly Detection in Industrial Machinery Using IoT Devices and Machine Learning: A Systematic Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, these studies do not cover the challenges involved in using ML for Anomaly Detection in industrial machinery within the context of the IoT ecosystems. This paper presents a systematic mapping study on Anomaly Detection for industrial machinery using IoT devices and ML algorithms to address this gap. |
SÉRGIO F. CHEVTCHENKO et. al. | arxiv-cs.LG | 2023-07-28 |
| 251 | Earthquake Electromagnetic Precursor Anomaly Detection Method Based on Empirical Mode Decomposition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposes an anomaly detection method based on the combination of empirical mode decomposition (EMD) and sliding Interquartile range (SIQR) for detecting electromagnetic … |
Bangjie Xu; Yongming Huang; Yong Lu; Hongyu Li; | International Conference on Applied Mathematics, Modelling … | 2023-07-28 |
| 252 | BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, state-of-the-art GAD methods, such as CoLA and SL-GAD, heavily rely on negative pair sampling in contrastive learning, which incurs high computational costs, hindering their scalability to large graphs. To address these limitations, we propose a novel unified graph anomaly detection framework based on bootstrapped self-supervised learning (named BOURNE). |
JIE LIU et. al. | arxiv-cs.SI | 2023-07-27 |
| 253 | Coupled-Space Attacks Against Random-Walk-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Consequently, there are two potential attack surfaces against RWAD: graph-space attacks and feature-space attacks. In this paper, we explore this vulnerability by designing practical coupled-space attacks, investigating the interplay between graph-space and feature-space attacks. |
YUNI LAI et. al. | arxiv-cs.CR | 2023-07-26 |
| 254 | EasyNet: An Easy Network for 3D Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Extensive experiments show that EasyNet achieves an anomaly detection AUROC of 92.6% without using pre-trained models and memory banks. |
RUITAO CHEN et. al. | arxiv-cs.CV | 2023-07-25 |
| 255 | RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, they still suffer from two limitations: 1) unlabeled anomalies (i.e., anomaly contamination) may mislead the learning process when all the unlabeled data are employed as inliers for model training; 2) only discrete supervision information (such as binary or ordinal data labels) is exploited, which leads to suboptimal learning of anomaly scores that essentially take on a continuous distribution. Therefore, this paper proposes a novel semi-supervised anomaly detection method, which devises \textit{contamination-resilient continuous supervisory signals}. |
HONGZUO XU et. al. | arxiv-cs.LG | 2023-07-25 |
| 256 | Construction of Data-Driven Performance Digital Twin for A Real-World Gas Turbine Anomaly Detection Considering Uncertainty Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection and failure prediction of gas turbines is of great importance for ensuring reliable operation. This work presents a novel approach for anomaly detection based on … |
Yangfeifei Ma; Xinyun Zhu; Jilong Lu; Pan Yang; Jianzhong Sun; | Sensors (Basel, Switzerland) | 2023-07-25 |
| 257 | Integration of Digital Twin and Federated Learning for Securing Vehicular Internet of Things Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a Hierarchical Federated Learning (HFL) based anomaly detection model for V-IoT, aiming to enhance the accuracy of the model. |
Deepti Gupta; Shafika Showkat Moni; Ali Saman Tosun; | arxiv-cs.CR | 2023-07-25 |
| 258 | AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by a modern self-supervised vision transformer model trained using partial image inputs to reconstruct missing image regions — we propose AMAE, a two-stage algorithm for adaptation of the pre-trained masked autoencoder (MAE). |
Behzad Bozorgtabar; Dwarikanath Mahapatra; Jean-Philippe Thiran; | arxiv-cs.CV | 2023-07-24 |
| 259 | UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present UniFormaly, a universal and powerful anomaly detection framework. |
Yujin Lee; Harin Lim; Seoyoon Jang; Hyunsoo Yoon; | arxiv-cs.CV | 2023-07-24 |
| 260 | Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, retrieving anomalous events using detailed descriptions is practical and positive but few researches focus on this. In this context, we propose a novel task called Video Anomaly Retrieval (VAR), which aims to pragmatically retrieve relevant anomalous videos by cross-modalities, e.g., language descriptions and synchronous audios. |
PENG WU et. al. | arxiv-cs.CV | 2023-07-24 |
| 261 | Using An Anomaly Detection Approach for The Segmentation of Colorectal Cancer Tumors in Whole Slide Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proposed approach provides an automated CRC tumor segmentation pipeline with a quantitatively reproducible quality compared with the conventional manual tumor segmentation procedure. |
Q. GU et. al. | med.pathology | 2023-07-23 |
| 262 | TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we only assume access to contaminated data and present a diffusion-based probabilistic model effective for unsupervised anomaly detection. |
Guy Zamberg; Moshe Salhov; Ofir Lindenbaum; Amir Averbuch; | arxiv-cs.LG | 2023-07-23 |
| 263 | RegraphGAN: A Graph Generative Adversarial Network Model for Dynamic Network Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the wide application of dynamic graph anomaly detection in cybersecurity, social networks, e-commerce, etc., research in this area has received increasing attention. Graph … |
Dezhi Guo; Zhaowei Liu; Ranran Li; | Neural networks : the official journal of the International … | 2023-07-20 |
| 264 | Ensemble Learning Based Anomaly Detection for IoT Cybersecurity Via Bayesian Hyperparameters Sensitivity Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive study on using ensemble machine learning methods for enhancing IoT cybersecurity via anomaly detection. |
Tin Lai; Farnaz Farid; Abubakar Bello; Fariza Sabrina; | arxiv-cs.LG | 2023-07-20 |
| 265 | FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present FACADE, a novel probabilistic and geometric framework designed for unsupervised mechanistic anomaly detection in deep neural networks. |
Dhruv Pai; Andres Carranza; Rylan Schaeffer; Arnuv Tandon; Sanmi Koyejo; | arxiv-cs.LG | 2023-07-20 |
| 266 | Performance Issue Identification in Cloud Systems with Relational-Temporal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Moreover, there exist some unlabeled anomalies mixed in the training data, which may hinder the detection performance. To address these limitations, we propose the Relational- Temporal Anomaly Detection Model (RTAnomaly) that combines the relational and temporal information of metrics. |
WENWEI GU et. al. | arxiv-cs.LG | 2023-07-20 |
| 267 | Representation Learning in Anomaly Detection: Successes, Limits and A Grand Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this perspective paper, we argue that the dominant paradigm in anomaly detection cannot scale indefinitely and will eventually hit fundamental limits. |
Yedid Hoshen; | arxiv-cs.LG | 2023-07-20 |
| 268 | Refining The Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a comprehensive framework for automatic parameter optimization in time series anomaly detection models. |
MANQING DONG et. al. | arxiv-cs.LG | 2023-07-20 |
| 269 | Matrix Profile Based Anomaly Detection in Streaming Gait Data for Fall Prevention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a gait anomaly detection system based on the Matrix Profile (MP) algorithm. |
BRANISLAV GERAZOV et. al. | arxiv-eess.SP | 2023-07-18 |
| 270 | Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing approaches for this problem mostly employ either statistical models which cannot capture the non-linear relations well or conventional deep learning models (e.g., CNN and LSTM) that do not explicitly learn the pairwise correlations among variables. To overcome these limitations, we propose a novel method, correlation-aware spatial-temporal graph learning (termed CST-GL), for time series anomaly detection. |
YU ZHENG et. al. | arxiv-cs.LG | 2023-07-17 |
| 271 | Passenger Flow Anomaly Detection in Urban Rail Transit Networks with Graph Convolution Network-informer and Gaussian Bayes Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article proposes a novel anomaly detection methodology based on a deep learning framework consisting of a graph convolution network (GCN)-informer model and a Gaussian naive Bayes model. |
Bing Liu; Xiaolei Ma; Erlong Tan; Zhenliang Ma; | Philosophical transactions. Series A, Mathematical, … | 2023-07-17 |
| 272 | Anomaly Detection with Selective Dictionary Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we present new methods of anomaly detection based on Dictionary Learning (DL) and Kernel Dictionary Learning (KDL). |
Denis C. Ilie-Ablachim; Bogdan Dumitrescu; | arxiv-cs.LG | 2023-07-17 |
| 273 | LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the context of flexible manufacturing systems that are required to produce different types and quantities of products with minimal reconfiguration, this paper addresses the problem of unsupervised multi-class anomaly detection: develop a unified model to detect anomalies from objects belonging to multiple classes when only normal data is accessible. |
HAONAN YIN et. al. | arxiv-cs.CV | 2023-07-16 |
| 274 | COOpD: Reformulating COPD Classification on Chest CT Scans As Anomaly Detection Using Contrastive Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We reformulate COPD binary classification as an anomaly detection task, proposing cOOpD: heterogeneous pathological regions are detected as Out-of-Distribution (OOD) from normal homogeneous lung regions. |
SILVIA D. ALMEIDA et. al. | arxiv-eess.IV | 2023-07-14 |
| 275 | Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal. |
ALESSANDRO FLABOREA et. al. | arxiv-cs.CV | 2023-07-14 |
| 276 | Weakly Supervised Marine Animal Detection from Remote Sensing Images Using Vector-quantized Variational Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such an approach leverages an anomaly detection framework that computes metrics directly on the input space, enhancing interpretability and anomaly localization compared to feature embedding methods. Building upon the success of Vector-Quantized Variational Autoencoders in anomaly detection on computer vision datasets, we adapt them to the marine animal detection domain and address the challenge of handling noisy data. |
Minh-Tan Pham; Hugo Gangloff; Sébastien Lefèvre; | arxiv-cs.CV | 2023-07-13 |
| 277 | Visualization for Multivariate Gaussian Anomaly Detection in Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a simplified variation of the PaDiM (Pixel-Wise Anomaly Detection through Instance Modeling) method for anomaly detection in images, fitting a single multivariate Gaussian (MVG) distribution to the feature vectors extracted from a backbone convolutional neural network (CNN) and using their Mahalanobis distance as the anomaly score. |
Joao P C Bertoldo; David Arrustico; | arxiv-cs.CV | 2023-07-12 |
| 278 | Personalized Anomaly Detection in PPG Data Using Representation Learning and Biometric Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a two-stage framework leveraging representation learning and personalization to improve anomaly detection performance in PPG data. |
Ramin Ghorbani; Marcel J. T. Reinders; David M. J. Tax; | arxiv-cs.LG | 2023-07-12 |
| 279 | DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose DSV (Discordance and Separability Validation), an unsupervised validation loss to select high-performing detection models with effective augmentation HPs. |
Jaemin Yoo; Yue Zhao; Lingxiao Zhao; Leman Akoglu; | arxiv-cs.LG | 2023-07-12 |
| 280 | Retracted: Time Series Anomaly Detection Model Based on Multi-Features Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: [This retracts the article DOI: 10.1155/2022/2371549.]. … |
Computational Intelligence And Neuroscience; | Computational intelligence and neuroscience | 2023-07-12 |
| 281 | A Self-Supervised Anomaly Detector of Fruits Based on Hyperspectral Imaging Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Hyperspectral imaging combined with chemometric approaches is proven to be a powerful tool for the quality evaluation and control of fruits. In fruit defect-detection scenarios, … |
YISEN LIU et. al. | Foods (Basel, Switzerland) | 2023-07-11 |
| 282 | Temporal Graphs Anomaly Emergence Detection: Benchmarking For Social Media Interactions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive benchmarking study that compares 12 data-driven methods for anomaly detection in temporal graphs. |
Teddy Lazebnik; Or Iny; | arxiv-cs.SI | 2023-07-11 |
| 283 | Performance Comparison of Timing-based Anomaly Detectors for Controller Area Network: A Reproducible Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents an experimental evaluation of the detection performance of eight different algorithms for anomaly detection on the Controller Area Network (CAN) bus of modern vehicles based on the analysis of the timing or frequency of CAN messages. |
Francesco Pollicino; Dario Stabili; Mirco Marchetti; | arxiv-cs.CR | 2023-07-10 |
| 284 | PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In order to broaden the application and research of anomaly detection in unmanned supermarkets and smart manufacturing, we introduce the supermarket goods anomaly detection (GoodsAD) dataset. |
Jian Zhang; Runwei Ding; Miaoju Ban; Ge Yang; | arxiv-cs.CV | 2023-07-10 |
| 285 | Unsupervised Video Anomaly Detection Based on Similarity with Predefined Text Descriptions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Research on video anomaly detection has mainly been based on video data. However, many real-world cases involve users who can conceive potential normal and abnormal situations … |
Jaehyun Kim; Seongwook Yoon; Taehyeon Choi; Sanghoon Sull; | Sensors (Basel, Switzerland) | 2023-07-09 |
| 286 | Improving Visual Defect Detection and Localization in Industrial Thermal Images Using Autoencoders Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Reliable functionality in anomaly detection in thermal image datasets is crucial for defect detection of industrial products. Nevertheless, achieving reliable functionality is … |
SASHA BEHROUZI et. al. | Journal of imaging | 2023-07-07 |
| 287 | Noise-to-Norm Reconstruction for Industrial Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, a reconstruction-based method using the noise-to-norm paradigm is proposed, which avoids the invariant reconstruction of anomalous regions. |
Shiqi Deng; Zhiyu Sun; Ruiyan Zhuang; Jun Gong; | arxiv-cs.CV | 2023-07-06 |
| 288 | Contextual Affinity Distillation for Image Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, based on previous knowledge distillation works, we propose to use two students (local and global) to better mimic the teacher’s behavior. |
Jie Zhang; Masanori Suganuma; Takayuki Okatani; | arxiv-cs.CV | 2023-07-06 |
| 289 | That’s BAD: Blind Anomaly Detection By Implicit Local Feature Clustering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we consider a more challenging scenario of unsupervised AD, in which we detect anomalies in a given set of images that might contain both normal and anomalous samples. |
Jie Zhang; Masanori Suganuma; Takayuki Okatani; | arxiv-cs.CV | 2023-07-06 |
| 290 | Prototypes As Explanation for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes ProtoAD, using prototypes as the example-based explanation for the state of regular patterns during anomaly detection. |
Bin Li; Carsten Jentsch; Emmanuel Müller; | arxiv-cs.LG | 2023-07-04 |
| 291 | The ROAD to Discovery: Machine Learning-driven Anomaly Detection in Radio Astronomy Spectrograms Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present the Radio Observatory Anomaly Detector (ROAD), a framework that combines both SSL-based anomaly detection and a supervised classification, thereby enabling both classification of both commonly occurring anomalies and detection of unseen anomalies. |
MICHAEL MESARCIK et. al. | arxiv-astro-ph.IM | 2023-07-03 |
| 292 | Feasibility of Universal Anomaly Detection Without Knowing The Abnormality in Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, even though only the normal images were used in the training process, the abnormal images were often employed during the validation process (e.g., epoch selection, hyper-parameter tuning), which might leak the supposed “unknown abnormality unintentionally. In this study, we investigated these two essential aspects regarding universal anomaly detection in medical images by (1) comparing various anomaly detection methods across four medical datasets, (2) investigating the inevitable but often neglected issues on how to unbiasedly select the optimal anomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. |
CAN CUI et. al. | arxiv-cs.CV | 2023-07-03 |
| 293 | ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing approaches, including forecasting and reconstruction-based methods, struggle to address these challenges effectively. To overcome these limitations, we propose a novel anomaly detection framework named ImDiffusion, which combines time series imputation and diffusion models to achieve accurate and robust anomaly detection. |
YUHANG CHEN et. al. | arxiv-cs.LG | 2023-07-03 |
| 294 | Graph Neural Networks Based Log Anomaly Detection and Explanation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unfortunately, only considering quantitative or sequential relationships may result in low detection accuracy. To alleviate this problem, we propose a graph-based method for unsupervised log anomaly detection, dubbed Logs2Graphs, which first converts event logs into attributed, directed, and weighted graphs, and then leverages graph neural networks to perform graph-level anomaly detection. |
Zhong Li; Jiayang Shi; Matthijs van Leeuwen; | arxiv-cs.SE | 2023-07-02 |
| 295 | A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera Views Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Therefore, weakly supervised methods are heavily researched for this application. In this paper, we tackle these typical problems of anomaly detection in surveillance video by combining Multiple Instance Learning (MIL) to deal with the lack of labels and Multiple Camera Views (MC) to reduce occlusion and clutter effects. |
Silas Santiago Lopes Pereira; José Everardo Bessa Maia; | arxiv-cs.CV | 2023-07-02 |
| 296 | Retraction Notice to ‘Personalized Federated Learning Framework for Network Traffic Anomaly Detection’ IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jiaming Pei; Kaiyang Zhong; M. Jan; Jinhai Li; | Comput. Networks | 2023-07-01 |
| 297 | Prior-based Collaborative Representation with Global Adaptive Weight for Hyperspectral Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstract. Hyperspectral anomaly detection (HAD) is a technique to find observations without prior knowledge, which is of particular interest as a branch of remote sensing object … |
NAN WANG et. al. | Journal of Applied Remote Sensing | 2023-07-01 |
| 298 | Applied Bayesian Structural Health Monitoring: Inclinometer Data Anomaly Detection and Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we apply Uncertainty Quantification (UQ) techniques by implementing a Bayesian approach to anomaly detection and forecasting for inclinometer data. |
David K. E. Green; Adam Jaspan; | arxiv-cs.LG | 2023-07-01 |
| 299 | Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Different from current reconstruction-guided generative models and transformation-based contrastive models, we devise novel data-driven supervision for tabular data by introducing a characteristic — scale — as data labels. |
HONGZUO XU et. al. | icml | 2023-06-27 |
| 300 | Estimating The Contamination Factor’s Distribution in Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unfortunately, there are no good methods for estimating the contamination factor itself. We address this need from a Bayesian perspective, introducing a method for estimating the posterior distribution of the contamination factor for a given unlabeled dataset. |
Lorenzo Perini; Paul-Christian Bürkner; Arto Klami; | icml | 2023-06-27 |
| 301 | Precursor-of-Anomaly Detection for Irregular Time Series Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a novel type of anomaly detection, called Precursor-of-Anomaly (PoA) detection. |
Sheo Yon Jhin; Jaehoon Lee; Noseong Park; | arxiv-cs.AI | 2023-06-27 |
| 302 | Prototype-oriented Unsupervised Anomaly Detection for Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing UAD methods try to learn a fixed set of mappings for each MTS, entailing expensive computation and limited model adaptation. To address this pivotal issue, we propose a prototype-oriented UAD (PUAD) method under a probabilistic framework. |
YUXIN LI et. al. | icml | 2023-06-27 |
| 303 | Anomaly Detection of Terminal Access Based on LSTM and ResNet Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Massive wireless debugging terminals and complex and diverse access requirements pose significant challenges to the secure access of substation terminal equipment. It is crucial … |
Nige Li; Yong Li; Ziang Lu; Duanchao Li; Jinjin Ding; | Other Conferences | 2023-06-26 |
| 304 | Cross-Domain Graph Anomaly Detection Via Anomaly-Aware Contrastive Alignment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we introduce a novel domain adaptation approach, namely Anomaly-aware Contrastive alignmenT (ACT), for GAD. |
Qizhou Wang; Guansong Pang; Mahsa Salehi; Wray Buntine; Christopher Leckie; | aaai | 2023-06-26 |
| 305 | Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We observe that such a scheme is sub-optimal, i.e., for better distinguishing anomaly one needs to understand what is a normal state, and may yield a higher false alarm rate. To address this issue, we propose an Uncertainty Regulated Dual Memory Units (UR-DMU) model to learn both the representations of normal data and discriminative features of abnormal data. |
Hang Zhou; Junqing Yu; Wei Yang; | aaai | 2023-06-26 |
| 306 | Detecting Multivariate Time Series Anomalies with Zero Known Label Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose MTGFlow, an unsupervised anomaly detection approach forMultivariate Time series anomaly detection via dynamic Graph and entityaware normalizing Flow, leaning only on a widely accepted hypothesis that abnormal instances exhibit sparse densities than the normal. |
Qihang Zhou; Jiming Chen; Haoyu Liu; Shibo He; Wenchao Meng; | aaai | 2023-06-26 |
| 307 | Learning Event-Relevant Factors for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to explicitly learn event-relevant factors to eliminate the interferences from event-irrelevant factors on anomaly predictions. |
Che Sun; Chenrui Shi; Yunde Jia; Yuwei Wu; | aaai | 2023-06-26 |
| 308 | ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a method to leverage weak/noisy labels (e.g., risk scores generated by machine rules for detecting malware) that are cheaper to obtain for anomaly detection. |
Yue Zhao; Guoqing Zheng; Subhabrata Mukherjee; Robert McCann; Ahmed Awadallah; | aaai | 2023-06-26 |
| 309 | KPI Anomaly Detection Method of AIOps Based on GAN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To ensure the stable running of systems and services in a data center, O&M engineers need to collect and monitor Key Performance indicators (KPIs) generated during system and … |
Zhehang Yu; Yanyun Fu; Wenxi Shi; Xueyi Zhao; Yong Yang; | Other Conferences | 2023-06-26 |
| 310 | MGFN: Magnitude-Contrastive Glance-and-Focus Network for Weakly-Supervised Video Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In addition, we empirically found that existing approaches that use feature magnitudes to represent the degree of anomalies typically ignore the effects of scene variations, and hence result in sub-optimal performance due to the inconsistency of feature magnitudes across scenes. To address this issue, we propose the Feature Amplification Mechanism and a Magnitude Contrastive Loss to enhance the discriminativeness of feature magnitudes for detecting anomalies. |
YINGXIAN CHEN et. al. | aaai | 2023-06-26 |
| 311 | One-for-All: Proposal Masked Cross-Class Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One of the most challenges for anomaly detection (AD) is how to learn one unified and generalizable model to adapt to multi-class especially cross-class settings: the model is trained with normal samples from seen classes with the objective to detect anomalies from both seen and unseen classes. In this work, we propose a novel Proposal Masked Anomaly Detection (PMAD) approach for such challenging multi- and cross-class anomaly detection. |
Xincheng Yao; Chongyang Zhang; Ruoqi Li; Jun Sun; Zhenyu Liu; | aaai | 2023-06-26 |
| 312 | Mean-Shifted Contrastive Loss for Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We take the approach of transferring representations pre-trained on external datasets for anomaly detection. |
Tal Reiss; Yedid Hoshen; | aaai | 2023-06-26 |
| 313 | Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a weakly supervised anomaly detection framework that emphasizes efficient context modeling and enhanced semantic discriminability. |
Yujiang Pu; Xiaoyu Wu; Shengjin Wang; | arxiv-cs.CV | 2023-06-26 |
| 314 | Targeted Collapse Regularized Autoencoder for Anomaly Detection: Black Hole at The Center Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a remarkably straightforward alternative: instead of adding neural network components, involved computations, and cumbersome training, we complement the reconstruction loss with a computationally light term that regulates the norm of representations in the latent space. |
AMIN GHAFOURIAN et. al. | arxiv-cs.LG | 2023-06-21 |
| 315 | End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce ST-SSAD (Self-Tuning Self-Supervised Anomaly Detection), the first systematic approach to SSAD in regards to rigorously tuning augmentation. |
Jaemin Yoo; Lingxiao Zhao; Leman Akoglu; | arxiv-cs.LG | 2023-06-21 |
| 316 | BMAD: Benchmarks for Medical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, there is a lack of a universal and fair benchmark for evaluating AD methods on medical images, which hinders the development of more generalized and robust AD methods in this specific domain. To bridge this gap, we introduce a comprehensive evaluation benchmark for assessing anomaly detection methods on medical images. |
JINAN BAO et. al. | arxiv-eess.IV | 2023-06-20 |
| 317 | Non-contact Sensing for Anomaly Detection in Wind Turbine Blades: A Focus-SVDD with Complex-Valued Auto-Encoder Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we enhance the quality assurance of manufacturing utilizing FMCW radar as a non-destructive sensing modality. |
Gaëtan Frusque; Daniel Mitchell; Jamie Blanche; David Flynn; Olga Fink; | arxiv-eess.SP | 2023-06-19 |
| 318 | Machine Learning for Real-Time Anomaly Detection in Optical Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes a real-time anomaly detection scheme that leverages the multi-step ahead prediction capabilities of encoder-decoder (ED) deep learning models with recurrent units. |
Sadananda Behera; Tania Panayiotou; Georgios Ellinas; | arxiv-cs.LG | 2023-06-19 |
| 319 | Improving Generalizability of Graph Anomaly Detection Models Via Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we base on the phenomenon and propose a general and novel research problem of generalized graph anomaly detection that aims to effectively identify anomalies on both the training-domain graph and unseen testing graph to eliminate potential dangers. |
SHUANG ZHOU et. al. | arxiv-cs.LG | 2023-06-18 |
| 320 | A Circuit-Level Solution for Secure Temperature Sensor Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Temperature sensors play an important role in modern monitoring and control applications. When more and more sensors are integrated into internet-connected systems, the integrity … |
Mashrafi Alam Kajol; Mohammad Mezanur Rahman Monjur; Qiaoyan Yu; | Sensors (Basel, Switzerland) | 2023-06-18 |
| 321 | DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose DCdetector, a multi-scale dual attention contrastive representation learning model. |
Yiyuan Yang; Chaoli Zhang; Tian Zhou; Qingsong Wen; Liang Sun; | arxiv-cs.LG | 2023-06-17 |
| 322 | An Effective Network Traffic Anomaly Detection Method Based on Deep Learning for Low-orbit Satellite Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the development of satellite networking technology, low-orbit satellites are gradually facing security threats caused by abnormal traffic. Since some types of attack traffic … |
Jiankai Wang; Liming Wang; Zhen Xu; | Intelligent Systems, Communications, and Computer Networks | 2023-06-16 |
| 323 | Multivariate Time-series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomalies are rare items that differ significantly from the majority of the data and raise suspicion. Time series anomaly detection is of great significance in industrial … |
Qifa Wang; Qiwei Shen; | Intelligent Systems, Communications, and Computer Networks | 2023-06-16 |
| 324 | MixedTeacher : Knowledge Distillation for Fast Inference Textural Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new method based on the promising concept of knowledge distillation which consists of training a network (the student) on normal samples while considering the output of a larger pretrained network (the teacher). |
Simon Thomine; Hichem Snoussi; Mahmoud Soua; | arxiv-cs.CV | 2023-06-16 |
| 325 | Anomaly Detection and Correction of Optimizing Autonomous Systems With Inverse Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article considers autonomous systems whose behaviors seek to optimize an objective function. |
BOSEN LIAN et. al. | IEEE transactions on cybernetics | 2023-06-15 |
| 326 | 2nd Place Winning Solution for The CVPR2023 Visual Anomaly and Novelty Detection Challenge: Multimodal Prompting for Data-centric Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This technical report introduces the winning solution of the team Segment Any Anomaly for the CVPR2023 Visual Anomaly and Novelty Detection (VAND) challenge. |
YUNKANG CAO et. al. | arxiv-cs.CV | 2023-06-15 |
| 327 | Hybrid Anomaly Detection Model on Trusted IoT Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Most machine learning proposals in the Internet of Things (IoT) are designed and evaluated on preprocessed data sets, where data acquisition and cleaning steps are often … |
P. Rosero-Montalvo; Z. István; Pınar Tözün; Wilmar Hernández; | IEEE Internet of Things Journal | 2023-06-15 |
| 328 | Investigating The Effectiveness of Novel Support Vector Neural Network for Anomaly Detection in Digital Forensics Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As criminal activity increasingly relies on digital devices, the field of digital forensics plays a vital role in identifying and investigating criminals. In this paper, we … |
UMAR ISLAM et. al. | Sensors (Basel, Switzerland) | 2023-06-15 |
| 329 | Correction: Flow-based Intrusion Detection on Software-defined Networks: A Multivariate Time Series Anomaly Detection Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sultan Zavrak; M. Iskefiyeli; | Neural Computing and Applications | 2023-06-15 |
| 330 | SaliencyCut: Augmenting Plausible Anomalies for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent wisdom of augmentation methods focuses on generating random pseudo instances that may lead to a mixture of augmented instances with seen anomalies, or out of the typical range of anomalies. To address this issue, we propose a novel saliency-guided data augmentation method, SaliencyCut, to produce pseudo but more common anomalies which tend to stay in the plausible range of anomalies. |
JIANAN YE et. al. | arxiv-cs.CV | 2023-06-14 |
| 331 | Hyperspectral Unmixing-based Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Research supporting improved anomaly detection performance benefits a wide range of technical applications, and thus, the definition of what anomalies are and the subsequent means … |
Mohammed S. H. Younis; M.A. Hossain; A. Robinson; Lan Wang; C. Preza; | Defense + Commercial Sensing | 2023-06-14 |
| 332 | Exploring The Tractability of Data Fusion Models for Detecting Anomalies in IoT-based Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years Internet of Things (IoT) devices have made their way into many different industries. Deep learning and machine learning methodologies have been applied to many … |
Devagopal A. M.; Vishal Menon; Soundararajan Ezekiel; Pankaj Chaudhary; | Defense + Commercial Sensing | 2023-06-14 |
| 333 | Low-level Anomaly Detection for Trace Explosives Using The Threat Anomaly Detection (ThreAD) Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Real-time analysis of data provides input for decision makers. However, in the battlefield, that could be the difference between life and death. Therefore, techniques must be … |
Eric R. Languirand; | Defense + Commercial Sensing | 2023-06-14 |
| 334 | Credit Card Fraud Detection Based on Unsupervised Attentional Anomaly Detection Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, with the rapid development of Internet technology, the number of credit card users has increased significantly. Subsequently, credit card fraud has caused a large … |
Shan Jiang; Ruiting Dong; Jie Wang; Min Xia; | Syst. | 2023-06-13 |
| 335 | No Free Lunch: The Hazards of Over-Expressive Representations in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we provide theoretical and empirical evidence to the contrary. |
Tal Reiss; Niv Cohen; Yedid Hoshen; | arxiv-cs.LG | 2023-06-12 |
| 336 | Coupled Attention Networks for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, MTAD is facing critical challenges deriving from the dependencies among sensors and variables, which often change over time. To address this issue, we propose a coupled attention-based neural network framework (CAN) for anomaly detection in multivariate time series data featuring dynamic variable relationships. |
FENG XIA et. al. | arxiv-cs.LG | 2023-06-12 |
| 337 | Anomaly Detection Method for Building Energy Consumption in Multivariate Time Series Based on Graph Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A critical issue in intelligent building control is detecting energy consumption anomalies based on intelligent device status data. The building field is plagued by energy … |
ZHE ZHANG et. al. | PloS one | 2023-06-08 |
| 338 | Log-based Anomaly Detection Based on EVT Theory with Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present an accurate, lightweight, and adaptive log-based anomaly detection framework, referred to as SeaLog. |
JINYANG LIU et. al. | arxiv-cs.SE | 2023-06-08 |
| 339 | Exploring Unsupervised Anomaly Detection with Quantum Boltzmann Machines in Fraud Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Allowing for the largest representation of data on available quantum hardware, we investigate Quantum Annealing based Quantum Boltzmann Machines (QBMs) for the given problem. We contribute the first fully unsupervised approach for the problem of anomaly detection using QBMs and evaluate its performance on a suitable synthetic dataset. |
JONAS STEIN et. al. | arxiv-quant-ph | 2023-06-08 |
| 340 | A Graph-based Approach to Video Anomaly Detection from The Perspective of Superpixels Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Video Anomaly Detection refers to the concept of discovering activities in a video feed that deviate from the usual visible pattern. It is a very well-studied and explored field … |
M. Siemon; Kamal Nasrollahi; T. Moeslund; | International Conference on Machine Vision | 2023-06-07 |
| 341 | Deep Learning for Predicting Future Lesion Emergence in High-risk Breast MRI Screening: A Feasibility Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our study, we tested the applicability of deep learning-based anomaly detection to identify anomalous changes in negative breast CE-MRI screens associated with future lesion emergence. In this prospective study, we trained a generative adversarial network on dynamic CE-MRI of 33 high-risk women who participated in a screening program but did not develop BC. |
BIANCA BURGER et. al. | European radiology experimental | 2023-06-07 |
| 342 | High-dimensional and Permutation Invariant Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce a permutation-invariant density estimator for particle physics data based on diffusion models, specifically designed to handle variable-length inputs. |
Vinicius Mikuni; Benjamin Nachman; | arxiv-hep-ph | 2023-06-06 |
| 343 | Anomaly Detection Techniques in Smart Grid Systems: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we provide a scoping review of research from the recent advancements in anomaly detection in the context of smart grids. |
Shampa Banik; Sohag Kumar Saha; Trapa Banik; S M Mostaq Hossain; | arxiv-cs.CR | 2023-06-04 |
| 344 | Disaster Anomaly Detector Via Deeper FCDDs for Explainable Initial Responses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an anomaly detection application utilizing deeper fully convolutional data descriptions (FCDDs), that enables the localization of devastation features and visualization of damage-marked heatmaps. |
Takato Yasuno; Masahiro Okano; Junichiro Fujii; | arxiv-cs.CV | 2023-06-04 |
| 345 | Exploring Global and Local Information for Anomaly Detection with Normal Samples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, in many realistic scenarios, only the samples following normal behavior are observed, while we can hardly obtain any anomaly information. To address such problem, we propose an anomaly detection method GALDetector which is combined of global and local information based on observed normal samples. |
Fan Xu; Nan Wang; Xibin Zhao; | arxiv-cs.LG | 2023-06-03 |
| 346 | GAD-NR: Graph Anomaly Detection Via Neighborhood Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As a result, they excel at detecting cluster-type structural anomalies but struggle with more complex structural anomalies that do not conform to clusters. To address this limitation, we propose a novel solution called GAD-NR, a new variant of GAE that incorporates neighborhood reconstruction for graph anomaly detection. |
AMIT ROY et. al. | arxiv-cs.LG | 2023-06-02 |
| 347 | Video Anomaly Detection System Using Deep Convolutional and Recurrent Models Related Papers Related Patents Related Grants Related Venues Related Experts View |
Maryam Qasim; Elena Verdú; | Results in Engineering | 2023-06-01 |
| 348 | Anomaly Detection With Representative Neighbors IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although many efforts have been made for anomaly detection, how to effectively handle high-dimensional data and how to exactly explore neighborhood information, a fundamental issue in anomaly detection, have not yet received sufficient concerns. To circumvent these challenges, in this article, we propose an effective anomaly detection method with representative neighbors for high-dimensional data. |
Huawen Liu; Xiaodan Xu; Enhui Li; Shichao Zhang; Xuelong Li; | IEEE transactions on neural networks and learning systems | 2023-06-01 |
| 349 | Anomaly Detection of Train Wheels Utilizing Short-time Fourier Transform and Unsupervised Learning Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ting Wan; C. Tsang; K. Hui; E. Chung; | Engineering Applications of Artificial Intelligence | 2023-06-01 |
| 350 | Cost-sensitive Random GBDT Based Anomaly Detection Method for Cloud Platform Traffic Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In order to solve the problem of low classification accuracy of the cloud platform anomaly detection model, this paper proposes a cost-sensitive random GBDT anomaly detection … |
L. Yu; Ruini Wang; | Other Conferences | 2023-06-01 |
| 351 | Anomaly Detection with Variance Stabilized Density Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Density estimation based anomaly detection schemes typically model anomalies as examples that reside in low-density regions. We propose a modified density estimation problem and demonstrate its effectiveness for anomaly detection. |
Amit Rozner; Barak Battash; Henry Li; Lior Wolf; Ofir Lindenbaum; | arxiv-cs.LG | 2023-06-01 |
| 352 | Multivariate Time Series Anomaly Detection Based on Graph Neural Network and Grated Neural Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multivariate time series anomaly detection aims to identify time periods in time series data that are abnormal or deviate from historical data patterns. The increasing dimension … |
Renbin Zhang; Zelin Zhou; Yicong Zuo; Yuhang Cui; Zishi Zhang; | Other Conferences | 2023-06-01 |
| 353 | Learning Hierarchical Spatial-Temporal Graph Representations for Robust Multivariate Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multivariate time series anomaly detection is one of the most indispensable yet troublesome links in complex industrial processes. The main challenge lies in discovering the … |
J. Yang; Zuogong Yue; | IEEE Transactions on Industrial Informatics | 2023-06-01 |
| 354 | Unsupervised Anomaly Detection Method Based on Deep Learning and Support Vector Data Description Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection in unlabelled and highly imbalanced high-dimensional monitoring data is one of the most urgent and challenging industry problems in the energy industry. Based on … |
WEIMING XU et. al. | Symposium on Advances in Electrical, Electronics and … | 2023-05-31 |
| 355 | Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection Through Automatic Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the current limitations in controlling noise granularity hinder diffusion models’ ability to generalize across diverse anomaly types and compromise the restoration of healthy tissues. To overcome these challenges, we propose AutoDDPM, a novel approach that enhances the robustness of diffusion models. |
Cosmin I. Bercea; Michael Neumayr; Daniel Rueckert; Julia A. Schnabel; | arxiv-cs.CV | 2023-05-31 |
| 356 | AnoOnly: Semi-Supervised Anomaly Detection with The Only Loss on Anomalies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the dominance of homogeneous normal data over anomalies biases the SSAD models against effectively perceiving anomalies. To address this issue and achieve balanced supervision between heavily imbalanced normal and abnormal data, we develop a novel framework called AnoOnly (Anomaly Only). |
YIXUAN ZHOU et. al. | arxiv-cs.LG | 2023-05-30 |
| 357 | Automated Screening of Computed Tomography Using Weakly Supervised Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Current artificial intelligence studies for supporting CT screening tasks depend on either supervised learning or detecting anomalies. However, the former involves a heavy … |
Atsuhiro Hibi; Michael D Cusimano; Alexander Bilbily; Rahul G Krishnan; Pascal N Tyrrell; | International journal of computer assisted radiology and … | 2023-05-29 |
| 358 | On Diffusion Modeling for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In particular, we find that Denoising Diffusion Probability Models (DDPM) are performant on anomaly detection benchmarks yet computationally expensive. |
Victor Livernoche; Vineet Jain; Yashar Hezaveh; Siamak Ravanbakhsh; | arxiv-cs.LG | 2023-05-29 |
| 359 | Truncated Affinity Maximization: One-class Homophily Modeling for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, this anomaly-discriminative property is ignored by existing GAD methods that are typically built using a conventional anomaly detection objective, such as data reconstruction. In this work, we explore this property to introduce a novel unsupervised anomaly scoring measure for GAD — local node affinity — that assigns a larger anomaly score to nodes that are less affiliated with their neighbors, with the affinity defined as similarity on node attributes/representations. |
Hezhe Qiao; Guansong Pang; | arxiv-cs.SI | 2023-05-29 |
| 360 | Unsupervised Road Anomaly Detection with Language Anchors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Road anomaly detection is critical to safe autonomous driving, because current road scene understanding models are usually trained in a closed-set manner and fail to identify … |
BEIWEN TIAN et. al. | 2023 IEEE International Conference on Robotics and … | 2023-05-29 |
| 361 | VLAD: Task-agnostic VAE-based Lifelong Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Lifelong learning represents an emerging machine learning paradigm that aims at designing new methods providing accurate analyses in complex and dynamic real-world environments. … |
Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz; | Neural networks : the official journal of the International … | 2023-05-27 |
| 362 | ReConPatch : Contrastive Patch Representation Learning for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce ReConPatch, which constructs discriminative features for anomaly detection by training a linear modulation attached to a pre-trained model. |
JEEHO HYUN et. al. | arxiv-cs.CV | 2023-05-26 |
| 363 | Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a weakly supervised anomaly detection system that has multiple contributions including a random batch selection mechanism to reduce interbatch correlation and a normalcy suppression block (NSB) 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; | IEEE transactions on neural networks and learning systems | 2023-05-26 |
| 364 | Impact of Log Parsing on Log-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we report on a comprehensive empirical study on the impact of log parsing on anomaly detection accuracy, using 13 log parsing techniques and five deep-learning-based anomaly detection techniques on two publicly available log datasets. |
Zanis Ali Khan; Donghwan Shin; Domenico Bianculli; Lionel Briand; | arxiv-cs.SE | 2023-05-25 |
| 365 | Anomaly Detection with Conditioned Denoising Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Denoising Diffusion Anomaly Detection (DDAD). |
Arian Mousakhan; Thomas Brox; Jawad Tayyub; | arxiv-cs.CV | 2023-05-25 |
| 366 | RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose RoLA, a real-time online lightweight anomaly detection system for multivariate time series based on a divide-and-conquer strategy, parallel processing, and the majority rule. |
Ming-Chang Lee; Jia-Chun Lin; | arxiv-cs.LG | 2023-05-25 |
| 367 | AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Anomaly Detection Neuroevolution (AD-NEv) – a scalable multi-level optimized neuroevolution framework for multivariate time series anomaly detection. |
Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo; | arxiv-cs.LG | 2023-05-25 |
| 368 | A Video Anomaly Detection Method with Mask Convolution and Channel Attention Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming at the problem of Insufficient feature extraction for data sets in video anomaly detection, an enhanced detection method combining masked convolution and channel attention … |
Dawei Yang; Zhiquan Liu; Haiyan Hao; | Conference on Machine Learning and Computer Application | 2023-05-25 |
| 369 | Research on Anomaly Network Detection Based on Self-Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Network traffic anomaly detection is a key step in identifying and preventing network security threats. This study aims to construct a new deep-learning-based traffic anomaly … |
Wanting Hu; Lu Cao; Qunsheng Ruan; Qingfeng Wu; | Sensors (Basel, Switzerland) | 2023-05-25 |
| 370 | Multiresolution Feature Guidance Based Transformer for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a multiresolution feature guidance method based on Transformer named GTrans for unsupervised anomaly detection and localization. |
SHUTING YAN et. al. | arxiv-cs.CV | 2023-05-24 |
| 371 | CLDTLog: System Log Anomaly Detection Method Based on Contrastive Learning and Dual Objective Tasks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: System logs are a crucial component of system maintainability, as they record the status of the system and essential events for troubleshooting and maintenance when necessary. … |
Gaoqi Tian; Nurbol Luktarhan; Haojie Wu; Zhaolei Shi; | Sensors (Basel, Switzerland) | 2023-05-24 |
| 372 | Deep Learning-Based Anomaly Detection in Video Surveillance: A Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection in video surveillance is a highly developed subject that is attracting increased attention from the research community. There is great demand for intelligent … |
Huu-Thanh Duong; Viet-Tuan Le; Vinh Truong Hoang; | Sensors (Basel, Switzerland) | 2023-05-24 |
| 373 | Towards Total Online Unsupervised Anomaly Detection and Localization in Industrial Vision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the first time, this paper presents a fully online learning image anomaly detection method, namely LeMO, learning memory for online image anomaly detection. |
Han Gao; Huiyuan Luo; Fei Shen; Zhengtao Zhang; | arxiv-cs.CV | 2023-05-24 |
| 374 | Audio-Visual Dataset and Method for Anomaly Detection in Traffic Videos Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the first audio-visual dataset for traffic anomaly detection taken from real-world scenes, called MAVAD, with a diverse range of weather and illumination conditions. |
BŁAŻEJ LEPOROWSKI et. al. | arxiv-cs.CV | 2023-05-24 |
| 375 | Unsupervised Anomaly Detection of Implausible Electronic Health Records: A Real-world Evaluation in Cancer Registries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unsupervised machine learning approaches can detect implausible electronic health records without human guidance. Therefore, this article investigates two unsupervised anomaly detection approaches, a pattern-based approach (FindFPOF) and a compression-based approach (autoencoder), to identify implausible electronic health records in cancer registries. |
Philipp Röchner; Franz Rothlauf; | BMC medical research methodology | 2023-05-24 |
| 376 | GAN-AE : An Anomaly Detection Algorithm for New Physics Search in LHC Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new Generative Adversarial Network-based auto-encoder model that allows both anomaly detection and model-independent background modeling. |
Louis Vaslin; Vincent Barra; Julien Donini; | arxiv-hep-ex | 2023-05-24 |
| 377 | Hazards&Robots: A Dataset for Visual Anomaly Detection in Robotics Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose Hazards&Robots, a dataset for Visual Anomaly Detection in Robotics. The dataset is composed of 324,408 RGB frames, and corresponding feature vectors; it contains … |
Dario Mantegazza; Alind Xhyra; Luca M Gambardella; Alessandro Giusti; Jérôme Guzzi; | Data in brief | 2023-05-24 |
| 378 | Beyond Individual Input for Deep Anomaly Detection on Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel deep anomaly detection method for tabular data that leverages Non-Parametric Transformers (NPTs), a model initially proposed for supervised tasks, to capture both feature-feature and sample-sample dependencies. |
Hugo Thimonier; Fabrice Popineau; Arpad Rimmel; Bich-Liên Doan; | arxiv-cs.LG | 2023-05-24 |
| 379 | Unsupervised Anomaly Detection for Cars CAN Sensors Time Series Using Small Recurrent and Convolutional Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Predictive maintenance in the car industry is an active field of research for machine learning and anomaly detection. The capability of cars to produce time series data from … |
Yann Cherdo; Benoit Miramond; Alain Pegatoquet; Alain Vallauri; | Sensors (Basel, Switzerland) | 2023-05-23 |
| 380 | Research on Abnormal Detection of Gas Load Based on LSTM-WGAN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Traditional anomaly detection methods cannot take into account the influence of external factors. Therefore, it is difficult to obtain an accurate detection effect when performing … |
Xiaofeng Xu; Xinbo Ai; Zhen Meng; | Other Conferences | 2023-05-23 |
| 381 | AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present AD-MERCS, an unsupervised approach to anomaly detection that explicitly aims at doing both. |
Jonas Soenen; Elia Van Wolputte; Vincent Vercruyssen; Wannes Meert; Hendrik Blockeel; | arxiv-cs.LG | 2023-05-22 |
| 382 | A New Comprehensive Benchmark for Semi-supervised Video Anomaly Detection and Anticipation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a new comprehensive dataset, NWPU Campus, containing 43 scenes, 28 classes of abnormal events, and 16 hours of videos. |
Congqi Cao; Yue Lu; Peng Wang; Yanning Zhang; | arxiv-cs.CV | 2023-05-22 |
| 383 | Anomaly Detection for Industrial Internet of Things Cyberattacks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rehab Alanazi; Ahamed Aljuhani; | Comput. Syst. Sci. Eng. | |
| 384 | LightESD: Fully-Automated and Lightweight Anomaly Detection Framework for Edge Computing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, deep learning models are typically iteratively optimized in a central server with input data gathered from edge devices, and such data transfer between edge devices and the central server impose substantial overhead on the network and incur additional latency and energy consumption. To overcome this problem, we propose a fully-automated, lightweight, statistical learning based anomaly detection framework called LightESD. |
Ronit Das; Tie Luo; | arxiv-cs.LG | 2023-05-20 |
| 385 | TTANAD: Test-Time Augmentation for Network Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This method aims to create additional points of view when examining network traffic during inference, making it suitable for a variety of anomaly detector algorithms. |
Seffi Cohen; Niv Goldshlager; Bracha Shapira; Lior Rokach; | Entropy (Basel, Switzerland) | 2023-05-19 |
| 386 | Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a new MIL framework: Unbiased MIL (UMIL), to learn unbiased anomaly features that improve WSVAD. |
HUI LV et. al. | cvpr | 2023-05-17 |
| 387 | Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we tackle supervised anomaly detection, i.e., we learn AD models using a few available anomalies with the objective to detect both the seen and unseen anomalies. |
Xincheng Yao; Ruoqi Li; Jing Zhang; Jun Sun; Chongyang Zhang; | cvpr | 2023-05-17 |
| 388 | SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. To exploit this structured information, we propose the use of Space-aware Memory Queues for In-painting and Detecting anomalies from radiography images (abbreviated as SQUID). |
TIANGE XIANG et. al. | cvpr | 2023-05-17 |
| 389 | Diversity-Measurable Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, to better solve the tradeoff problem, we propose Diversity-Measurable Anomaly Detection (DMAD) framework to enhance reconstruction diversity while avoid the undesired generalization on anomalies. |
Wenrui Liu; Hong Chang; Bingpeng Ma; Shiguang Shan; Xilin Chen; | cvpr | 2023-05-17 |
| 390 | MetaGAD: Learning to Meta Transfer for Few-shot Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the work exploring limited labeled anomalies and a large amount of unlabeled nodes in graphs to detect anomalies is rather limited. Therefore, in this paper, we study a novel problem of few-shot graph anomaly detection. |
Xiongxiao Xu; Kaize Ding; Canyu Chen; Kai Shu; | arxiv-cs.LG | 2023-05-17 |
| 391 | SimpleNet: A Simple Network for Image Anomaly Detection and Localization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a simple and application-friendly network (called SimpleNet) for detecting and localizing anomalies. |
Zhikang Liu; Yiming Zhou; Yuansheng Xu; Zilei Wang; | cvpr | 2023-05-17 |
| 392 | Self-Supervised Video Forensics By Audio-Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Manipulated videos often contain subtle inconsistencies between their visual and audio signals. We propose a video forensics method, based on anomaly detection, that can identify these inconsistencies, and that can be trained solely using real, unlabeled data. |
Chao Feng; Ziyang Chen; Andrew Owens; | cvpr | 2023-05-17 |
| 393 | OmniAL: A Unified CNN Framework for Unsupervised Anomaly Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a unified CNN framework for unsupervised anomaly localization, named OmniAL. |
Ying Zhao; | cvpr | 2023-05-17 |
| 394 | Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to solve the problem of the anomaly gap and scene gap by proposing a prompt-based feature mapping framework (PFMF). |
Zuhao Liu; Xiao-Ming Wu; Dian Zheng; Kun-Yu Lin; Wei-Shi Zheng; | cvpr | 2023-05-17 |
| 395 | Component-aware Anomaly Detection Framework for Adjustable and Logical Industrial Visual Inspection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, in this paper, we propose a novel component-aware anomaly detection framework (ComAD) which can simultaneously achieve adjustable and logical anomaly detection for industrial scenarios. |
TONGKUN LIU et. al. | arxiv-cs.CV | 2023-05-15 |
| 396 | Fast Model Update for IoT Traffic Anomaly Detection With Machine Unlearning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It is often needed to update deep learning-based detection models in traffic anomaly detection systems for the Internet of Things (IoT) because of mislabeled samples or device … |
Jiamin Fan; Kui Wu; Yang Zhou; Zhengan Zhao; Shengqiang Huang; | IEEE Internet of Things Journal | 2023-05-15 |
| 397 | Contrastive Learning with Prototype-Based Negative Mixing for Satellite Telemetry Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Telemetry data are the most important basis for ground operators to assess the status of satellites in orbit, and telemetry data-based anomaly detection has become a key tool to … |
Guohang Guo; Tai Hu; Taichun Zhou; Hu Li; Yurong Liu; | Sensors (Basel, Switzerland) | 2023-05-13 |
| 398 | Configurable Spatial-Temporal Hierarchical Analysis for Flexible Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unlike previous unsupervised VAD methods that adopt a fixed structure to learn normality without considering different detection demands, we design a spatial-temporal hierarchical architecture (STHA) as a configurable architecture to flexibly detect different degrees of anomaly. |
KAI CHENG et. al. | arxiv-cs.CV | 2023-05-12 |
| 399 | Special Issue on Unsupervised Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection (also known as outlier detection) is the task of finding instances in a dataset which deviate markedly from the norm […] … |
Markus Goldstein; | Applied Sciences | 2023-05-11 |
| 400 | Is AUC The Best Measure for Practical Comparison of Anomaly Detectors? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we question whether AUC is a good metric for anomaly detection, or if it gives a false sense of comfort, due to relying on assumptions which are unlikely to hold in practice. |
Vít Škvára; Tomáš Pevný; Václav Šmídl; | arxiv-cs.LG | 2023-05-08 |
| 401 | Supervised Anomaly Detection Via Conditional Generative Adversarial Network and Ensemble Active Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). |
Zhi Chen; Jiang Duan; Li Kang; Guoping Qiu; | IEEE transactions on pattern analysis and machine … | 2023-05-05 |
| 402 | Evaluation of Unsupervised Anomaly Detection Techniques in Labelling Epileptic Seizures on Human EEG Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automated labelling of epileptic seizures on electroencephalograms is an essential interdisciplinary task of diagnostics. Traditional machine learning approaches operate in a … |
O. E. KARPOV et. al. | Applied Sciences | 2023-05-04 |
| 403 | In-situ Anomaly Detection in Additive Manufacturing with Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study a model is trained on laser input information to predict nominal laser melting conditions. |
Sebastian Larsen; Paul A. Hooper; | arxiv-cs.CV | 2023-05-04 |
| 404 | Revisiting Graph Contrastive Learning for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the paper, we delve into the misconception and propose Multi-GNN and Augmented Graph contrastive framework MAG, which unified the existing GCAD methods in the contrastive self-supervised perspective. |
Zhiyuan Liu; Chunjie Cao; Fangjian Tao; Jingzhang Sun; | arxiv-cs.LG | 2023-05-03 |
| 405 | TAGAN: Multivariate Time Series Anomaly Detection Algorithm with Attention and Generative Adversarial Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, a new anomaly detection architecture, TAGAN, is proposed. By combining the reconstruction approach with the prediction approach, TAGAN is used for anomaly detection … |
Xinyu Jia; Wenbo Zhang; Xinzhi Yang; | International Conference on Electronic Information … | 2023-05-02 |
| 406 | Trace-based Microservice Anomaly Detection Through Deep Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Over the years, microservices have become increasingly popular and are being adopted more and more, microservice architecture is gradually replacing monolithic applications as the … |
Laigang Bai; Cheng Zhang; | International Conference on Electronic Information … | 2023-05-02 |
| 407 | Hyperspectral Anomaly Detection Using Ensemble and Robust Collaborative Representation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shaoxi Wang; Xintao Hu; J. Sun; Jinzhuo Liu; | Inf. Sci. | 2023-05-01 |
| 408 | Two-stage Reverse Knowledge Distillation Incorporated and Self-Supervised Masking Strategy for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
G. Tong; Quanquan Li; Yan Song; | Knowl. Based Syst. | 2023-05-01 |
| 409 | Federated Deep Learning for Anomaly Detection in The Internet of Things IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIAOFENG WANG et. al. | Comput. Electr. Eng. | 2023-05-01 |
| 410 | A Hybrid Deep Sensor Anomaly Detection for Autonomous Vehicles in 6G-V2X Environment Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Autonomous Vehicles (AVs) exchange real-time and seamless data between other AVs and the network, thus revolutionizing the Intelligent Transportation System (ITS). Automated … |
S. PRATHIBA et. al. | IEEE Transactions on Network Science and Engineering | 2023-05-01 |
| 411 | Anomaly Detection of Satellite Telemetry Data Based on Extended Dominant Sets Clustering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To mine out anomalies in satellite telemetry data under unsupervised conditions, a cluster-based method is proposed in this paper. Firstly, an extended dominant sets clustering … |
Xin Jin; Hui Wang; Zhonghe Jin; | Journal of Physics: Conference Series | 2023-05-01 |
| 412 | Research on Magnetic Anomaly Detection Method Assisted By Geomagnetic Map Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Magnetic anomaly detection is a detection technology for underwater/underground ferromagnetic targets. In the geomagnetic anomaly area, the change of magnetic feld is very … |
ZIQIANG YU et. al. | Journal of Physics: Conference Series | 2023-05-01 |
| 413 | Double Locality Sensitive Hashing Bloom Filter for High-dimensional Streaming Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhixia Zeng; Ruliang Xiao; Xinhong Lin; Tianjian Luo; Jiayin Lin; | Inf. Process. Manag. | 2023-05-01 |
| 414 | Video Surveillance for Indoor Office Environment Based on Object-Level Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Traditional methods of Abnormal Behavior Detection (ABD) process the surveillance video on frame-level, which ignores object-level abnormal behavior patterns. To address the … |
Haotian Chen; Chao Zhang; Zhouchen Lin; | Journal of Physics: Conference Series | 2023-05-01 |
| 415 | AnoFed: Adaptive Anomaly Detection for Digital Health Using Transformer-based Federated Learning and Support Vector Data Description Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ali Raza; K. Tran; L. Koehl; Shujun Li; | Eng. Appl. Artif. Intell. | 2023-05-01 |
| 416 | Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study we evaluate 32 unsupervised anomaly detection algorithms on 52 real-world multivariate tabular datasets, performing the largest comparison of unsupervised anomaly detection algorithms to date. |
Roel Bouman; Zaharah Bukhsh; Tom Heskes; | arxiv-cs.LG | 2023-05-01 |
| 417 | SLSG: Industrial Image Anomaly Detection By Learning Better Feature Embeddings and One-Class Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Focusing on more effective and comprehensive anomaly detection, we propose a network based on self-supervised learning and self-attentive graph convolution (SLSG) for anomaly detection. |
Minghui Yang; Jing Liu; Zhiwei Yang; Zhaoyang Wu; | arxiv-cs.CV | 2023-04-30 |
| 418 | Impact of Deep Learning Libraries on Online Adaptive Lightweight Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It might also mislead users in believing one approach is better than another. Therefore, in this paper, we investigate the impact of deep learning libraries on online adaptive lightweight time series anomaly detection by implementing two state-of-the-art anomaly detection approaches in three well-known deep learning libraries and evaluating how these two approaches are individually affected by the three deep learning libraries. |
Ming-Chang Lee; Jia-Chun Lin; | arxiv-cs.LG | 2023-04-30 |
| 419 | Unsupervised Anomaly Detection on Microservice Traces Through Graph VAE Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel dual-variable graph variational autoencoder (VAE) for unsupervised anomaly detection on microservice traces. |
ZHE XIE et. al. | www | 2023-04-29 |
| 420 | Network Traffic Anomaly Detection Method Based on Improved Clustering Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the surge in the amount of data transmitted on the network, intelligent learning and other technologies have emerged to solve the problem of anomaly detection of streaming … |
CHAOYANG XU et. al. | Conference on Signal Processing, Computer Networks, and … | 2023-04-28 |
| 421 | The Anomaly Behavior Detection Algorithm with Video-packet Attention in Transportation Surveillance Videos Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposes an end-to-end abnormal behavior detection network to detect strenuous movements in slow moving crowds, such as running, bicycling in transportation … |
LIYUAN WANG et. al. | International Conference on Artificial Intelligence and … | 2023-04-28 |
| 422 | Unsupervised Anomaly Detection and Localization of Machine Audio: A Gan-Based Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose AEGAN-AD, a totally unsupervised approach in which the generator (also an autoencoder) is trained to reconstruct input spectrograms. |
A. Jiang; W. -Q. Zhang; Y. Deng; P. Fan; J. Liu; | icassp | 2023-04-27 |
| 423 | Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple Yet Efficient Framework Based on Masked Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, even with only normal data training, the AEs often reconstruct anomalies well, which depletes their anomaly detection performance. To alleviate this issue, we propose a simple yet efficient framework for video anomaly detection. |
X. Huang; C. Zhao; C. Gao; L. Chen; Z. Wu; | icassp | 2023-04-27 |
| 424 | Two-Stream Decoder Feature Normality Estimating Network for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, these approaches are not explicitly optimized for distinguishable anomalies. To address these problems, we propose a two-stream decoder network (TSDN), designed to learn both normal and abnormal features. |
C. Park; M. Lee; S. Cho; D. Kim; S. Lee; | icassp | 2023-04-27 |
| 425 | Robust Hyperspectral Anomaly Detection with Simultaneous Mixed Noise Removal Via Constrained Convex Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a method to achieve robust anomaly detection even when HS images contain various types of noise. |
K. Sato; S. Ono; | icassp | 2023-04-27 |
| 426 | A Physically Explainable Framework for Human-Related Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce physically explainable dynamics to enhance visual representations. |
Y. Jiang; H. Li; C. Li; | icassp | 2023-04-27 |
| 427 | Robust Log-Based Anomaly Detection with Hierarchical Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, logs usually suffer from perturbations and it makes the existing log-based anomaly detection methods unstable. In this paper, we aim to solve this problem from the perspective of contrastive learning, by which the intrinsic and robust representations of logs are learned for anomaly detection. |
Y. ZHAO et. al. | icassp | 2023-04-27 |
| 428 | Relapse Detection in Patients with Psychotic Disorders Using Unsupervised Learning on Smartwatch Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present our solution for the ICASSP Signal Processing Grand Challenge e-Prevention track 2 Relapse Detection. |
S. Hamieh; V. Heiries; H. Al Osman; C. Godin; | icassp | 2023-04-27 |
| 429 | Robust Video Anomaly Detection Framework Via Prior Knowledge and Multi-Path Frame Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Video anomaly detection aims to automatically detect abnormal objects or behaviors. Most existing methods tackle the problem by minimizing the reconstruction errors stemming from … |
M. ZHANG et. al. | icassp | 2023-04-27 |
| 430 | FAPM: Fast Adaptive Patch Memory for Real-Time Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, some methods do not meet the speed requirements of real-time inference, which is crucial for real-world applications. To address this issue, we propose a new method called Fast Adaptive Patch Memory (FAPM) for real-time industrial anomaly detection. |
D. Kim; C. Park; S. Cho; S. Lee; | icassp | 2023-04-27 |
| 431 | Activity-Informed Industrial Audio Anomaly Detection Via Source Separation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This is particularly challenging since the interfering sounds are virtually indistinguishable from the target machine without additional information. To overcome these challenges, we fully exploit the information of machine activity or control that is easy to obtain in the industrial environment, and propose a framework of source separation (SS) followed by anomaly detection (AD), so called SSAD. |
J. KIM et. al. | icassp | 2023-04-27 |
| 432 | Low-Rank Constrained Memory Autoencoder for Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The process of constructing dictionary in these methods is complex and the stability of the models is hard to maintain. To address these problems, in this paper, we propose a low-rank constrained memory autoencoder (LRMAE) for HAD. |
Y. Lian; Y. Zhang; X. Feng; X. Jiang; Z. Cai; | icassp | 2023-04-27 |
| 433 | Smoothing Point Adjustment-Based Evaluation of Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes smoothing point adjustment, a novel range-based evaluation protocol for time series anomaly detection. |
M. LIU et. al. | icassp | 2023-04-27 |
| 434 | Quantum Generative Adversarial Networks For Anomaly Detection In High Energy Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The additional data complexity motivates the search for unsupervised anomaly detection methods that do not require prior knowledge about the underlying models. In this work, we develop such a technique. |
ELIE BERMOT et. al. | arxiv-quant-ph | 2023-04-27 |
| 435 | Learnable Flow Model Conditioned on Graph Representation Memory for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although invertible flow models are developed to accomplish unsupervised anomaly detection, they are usually hard to train and have limited capabilities of accurately modeling the distribution of normal samples. To address this problem, we propose a novel enhanced flow model conditioned on graph representation memory (FlowGRM) for visual surface defect detection. |
Z. Zhu; W. Liu; Z. Deng; | icassp | 2023-04-27 |
| 436 | Decentralized Real-Time Anomaly Detection in Cyber-Physical Production Systems Under Industry Constraints Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection is essential for realizing modern and secure cyber-physical production systems. By detecting anomalies, there is the possibility to recognize, react early, and … |
Christian Goetz; Bernhard Humm; | Sensors (Basel, Switzerland) | 2023-04-23 |
| 437 | An Optimization Framework For Anomaly Detection Scores Refinement With Side Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper considers an anomaly detection problem in which a detection algorithm assigns anomaly scores to multi-dimensional data points, such as cellular networks’ Key Performance Indicators (KPIs). We propose an optimization framework to refine these anomaly scores by leveraging side information in the form of a causality graph between the various features of the data points. |
ALI MAATOUK et. al. | arxiv-cs.IT | 2023-04-21 |
| 438 | Efficient L P Distance Computation Using Function-Hiding Inner Product Encryption for Privacy-Preserving Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a method to compute the Lp distance privately for even p>2 using inner product functional encryption and we use this method to compute an advanced metric, namely -powered error, for anomaly detection in a privacy-preserving manner. |
Dong-Hyeon Ryu; Seong-Yun Jeon; Junho Hong; Mun-Kyu Lee; | Sensors (Basel, Switzerland) | 2023-04-21 |
| 439 | An Attention Free Conditional Autoencoder For Anomaly Detection in Cryptocurrencies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To detect anomalies in the time series we have proposed an attention free conditional autoencoder (AF-CA). |
Hugo Inzirillo; Ludovic De Villelongue; | arxiv-cs.LG | 2023-04-20 |
| 440 | Interactive System-wise Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the challenges, we propose InterSAD (Interactive System-wise Anomaly Detection). |
Guanchu Wang; Ninghao Liu; Daochen Zha; Xia Hu; | arxiv-cs.LG | 2023-04-20 |
| 441 | Label-Free Anomaly Detection Using Distributed Optical Fiber Acoustic Sensing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, it is impossible to catalog all types of anomalies, therefore, the direct application of supervised learning is deficient. To overcome these problems, an unsupervised deep learning method that only learns the normal data features from ordinary events is proposed. |
Yuyuan Xie; Maoning Wang; Yuzhong Zhong; Lin Deng; Jianwei Zhang; | Sensors (Basel, Switzerland) | 2023-04-19 |
| 442 | Weakly Supervised Detection of Baby Cry Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose to use weakly supervised anomaly detection to detect a baby cry. |
Weijun Tan; Qi Yao; Jingfeng Liu; | arxiv-cs.CV | 2023-04-19 |
| 443 | Graph Neural Network-Based Anomaly Detection for River Network Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a solution to the challenging task of anomaly detection for river network sensor data, which is essential for accurate and continuous monitoring. |
Katie Buchhorn; Edgar Santos-Fernandez; Kerrie Mengersen; Robert Salomone; | arxiv-cs.LG | 2023-04-18 |
| 444 | One-Class SVM on Siamese Neural Network Latent Space for Unsupervised Anomaly Detection on Brain MRI White Matter Hyperintensities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose an unsupervised anomaly detection (UAD) method based on a latent space constructed by a siamese patch-based auto-encoder and perform the outlier detection with a One-Class SVM training paradigm tailored to the lesion detection task in multi-modality neuroimaging. |
Nicolas Pinon; Robin Trombetta; Carole Lartizien; | arxiv-eess.IV | 2023-04-17 |
| 445 | Exploring Exotic Configurations with Anomalous Features Using Deep Learning: Application of Classical and Quantum-classical Hybrid Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article we present the application of classical and quantum-classical hybrid anomaly detection schemes to explore exotic configuration with anomalous features. |
Kumar J. B. Ghosh; Sumit Ghosh; | arxiv-cond-mat.mes-hall | 2023-04-17 |
| 446 | Quantum Algorithm for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we present a quantum LOF algorithm consisting of three parts corresponding to the classical algorithm. |
MINGCHAO GUO et. al. | arxiv-quant-ph | 2023-04-17 |
| 447 | Exploring Exotic Configurations with Anomalous Features with Deep Learning: Application of Classical and Quantum-classical Hybrid Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this article we present the application of classical and quantum-classical hybrid anomaly detection schemes to explore exotic configuration with anomalous features. We consider … |
Kumar Ghosh; Sumit Ghosh; | Physical Review B | 2023-04-17 |
| 448 | Spot The Odd One Out: Regularized Complete Cycle Consistent Anomaly Detector GAN Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study presents an adversarial method for anomaly detection in real-world applications, leveraging the power of generative adversarial neural networks (GANs) through cycle consistency in reconstruction error. |
Zahra Dehghanian; Saeed Saravani; Maryam Amirmazlaghani; Mohammad Rahmati; | arxiv-cs.LG | 2023-04-16 |
| 449 | Few-shot Weakly-supervised Cybersecurity Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an enhancement to an existing few-shot weakly-supervised deep learning anomaly detection framework. |
Rahul Kale; Vrizlynn L. L. Thing; | arxiv-cs.CR | 2023-04-15 |
| 450 | Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nonetheless, as cancer is highly heterogeneous, it is challenging to train general-purpose discriminative cancer detection models, with data availability and disease complexity often cited as a limiting factor. |
ASHAY PATEL et. al. | arxiv-eess.IV | 2023-04-14 |
| 451 | Context-aware Domain Adaptation for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a framework that combines context sampling and anomaly detection into a joint learning procedure. |
KWEI-HERNG LAI et. al. | arxiv-cs.LG | 2023-04-14 |
| 452 | DCFF-MTAD: A Multivariate Time-Series Anomaly Detection Model Based on Dual-Channel Feature Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The detection of anomalies in multivariate time-series data is becoming increasingly important in the automated and continuous monitoring of complex systems and devices due to the … |
Zheng Xu; Yumeng Yang; Xinwen Gao; Min Hu; | Sensors (Basel, Switzerland) | 2023-04-12 |
| 453 | Exploring Diffusion Models for Unsupervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the performance of diffusion models for video anomaly detection (VAD) within the most challenging but also the most operational scenario in which the data annotations are not used. |
Anil Osman Tur; Nicola Dall’Asen; Cigdem Beyan; Elisa Ricci; | arxiv-cs.CV | 2023-04-12 |
| 454 | Metallogenic-Factor Variational Autoencoder for Geochemical Anomaly Detection By Ad-Hoc and Post-Hoc Interpretability Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zijing Luo; R. Zuo; Yihui Xiong; Bao Zhou; | Natural Resources Research | 2023-04-12 |
| 455 | Decoupling Anomaly Discrimination and Representation Learning: Self-supervised Learning for Anomaly Detection on Attributed Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, there are far fewer anomalous nodes than normal nodes, indicating a long-tailed data distribution. To address these challenges, a unique algorithm,Decoupled Self-supervised Learning forAnomalyDetection (DSLAD), is proposed in this paper. |
YANMING HU et. al. | arxiv-cs.LG | 2023-04-11 |
| 456 | Self-supervised Anomaly Detection, Staging and Segmentation for Retinal Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised anomaly detection (UAD) is to detect anomalies through learning the distribution of normal data without labels and therefore has a wide application in medical images … |
YIYUE LI et. al. | Medical image analysis | 2023-04-11 |
| 457 | Anomaly Detection in Automatic Meter Intelligence System Using Positive Unlabeled Learning and Multiple Symbolic Aggregate Approximation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the development of automatic electrical devices in smart grids, the data generated by time and transmitted are vast and thus impossible to control consumption by humans. The … |
Thi Ngoc Anh Nguyen; Hoai Thu Vu; Minh Tuan Dang; Dohyeun Kim; Anh Ngoc Le; | Big data | 2023-04-10 |
| 458 | AGAD: Adversarial Generative Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to address the lack of abnormal data for robust anomaly detection, we propose Adversarial Generative Anomaly Detection (AGAD), a self-contrast-based anomaly detection paradigm that learns to detect anomalies by generating \textit{contextual adversarial information} from the massive normal examples. |
Jian Shi; Ni Zhang; | arxiv-cs.CV | 2023-04-09 |
| 459 | An Efficient Framework for Unsupervised Anomaly Detection Over Edge-Assisted Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The detection of anomaly status plays a pivotal role in the maintenance of public transportation and facilities in smart cities. Owing to the pervasively deployed sensing devices, … |
Yumeng Liu; Hongan Wang; Xu Zheng; Ling Tian; | ACM Transactions on Sensor Networks | 2023-04-08 |
| 460 | Bridge Management Through Digital Twin-based Anomaly Detection Systems: A Systematic Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Bridge infrastructure has great economic, social, and cultural value. Nevertheless, many of the infrastructural assets are in poor conservation condition as has been recently … |
Alejandro Jiménez Rios; V. Plevris; M. Nogal; | Frontiers in Built Environment | 2023-04-07 |
| 461 | Unsupervised Learning of Healthy Anatomy for Anomaly Detection in Brain CT Scans Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic detection of abnormalities to assist radiologists in acute and screening scenarios has become a particular focus in medical imaging research. Various approaches have … |
Sina Walluscheck; Luca Canalini; J. Klein; S. Heldmann; | Medical Imaging | 2023-04-07 |
| 462 | Nanosecond Anomaly Detection with Decision Trees for High Energy Physics and Real-time Application to Exotic Higgs Decays Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel implementation of the artificial intelligence autoencoding algorithm, used as an ultrafast and ultraefficient anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. |
STEPHEN ROCHE et. al. | arxiv-hep-ex | 2023-04-07 |
| 463 | Siam-VAE: A Hybrid Deep Learning Based Anomaly Detection Framework for Automated Quality Control of Head CT Scans Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An automated quality control (QC) system is essential to ensure streamlined head computed tomography (CT) scan interpretations that do not affect subsequent image analysis. Such a … |
Soumyendu Ghosh; R. Dhar; D. Marcus; Aristeidis Sotiras; | Medical Imaging | 2023-04-07 |
| 464 | From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce ALARM (for Analyst-in-the-Loop Anomaly Reasoning and Management); an end-to-end framework that supports the anomaly mining cycle comprehensively, from detection to action. |
Xueying Ding; Nikita Seleznev; Senthil Kumar; C. Bayan Bruss; Leman Akoglu; | arxiv-cs.LG | 2023-04-06 |
| 465 | Wind Turbine Anomaly Detection Based on SCADA: A Deep Autoencoder Enhanced By Fault Instances Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An increasing number of deep autoencoder-based algorithms for intelligent condition monitoring and anomaly detection have been reported in recent years to improve wind turbine … |
JIARUI LIU et. al. | ISA transactions | 2023-04-06 |
| 466 | Toward Unsupervised 3D Point Cloud Anomaly Detection Using Variational Autoencoder IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. |
Mana Masuda; Ryo Hachiuma; Ryo Fujii; Hideo Saito; Yusuke Sekikawa; | arxiv-cs.CV | 2023-04-06 |
| 467 | Detection and Explanation of Anomalies in Healthcare Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a framework that detects anomalies in healthcare data and then provides an explanation of anomalies. |
Durgesh Samariya; Jiangang Ma; Sunil Aryal; Xiaohui Zhao; | Health information science and systems | 2023-04-06 |
| 468 | Industrial Anomaly Detection with Domain Shift: A Real-world Dataset and Masked Multi-scale Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing IAD datasets focus on the diversity of data categories, overlooking the diversity of domains within the same data category. In this paper, to bridge this gap, we propose the Aero-engine Blade Anomaly Detection (AeBAD) dataset, consisting of two sub-datasets: the single-blade dataset and the video anomaly detection dataset of blades. |
Zilong Zhang; Zhibin Zhao; Xingwu Zhang; Chuang Sun; Xuefeng Chen; | arxiv-cs.CV | 2023-04-05 |
| 469 | Publisher Correction: Unsupervised Anomaly Detection with Generative Adversarial Networks in Mammography Related Papers Related Patents Related Grants Related Venues Related Experts View |
Seungju Park; Kyung Hwa Lee; Beomseok Ko; Namkug Kim; | Scientific reports | 2023-04-05 |
| 470 | Detecting Anomalous Proteins Using Deep Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Many of these proteins unique properties were discovered by manual inspection, which is becoming infeasible at the scale of modern protein datasets. Here, we propose to tackle this challenge using anomaly detection methods that automatically identify unexpected properties. |
T. Michael-Pitschaze; N. Cohen; D. Ofer; Y. Hoshen; M. Linial; | bio.bioinformatics | 2023-04-05 |
| 471 | Individualized Statistical Modeling of Lesions in Fundus Images for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection in fundus images remains challenging due to the fact that fundus images often contain diverse types of lesions with various properties in locations, sizes, … |
YUCHEN DU et. al. | IEEE transactions on medical imaging | 2023-04-03 |
| 472 | Simulation Based Evaluation Framework for Deep Learning Unsupervised Anomaly Detection on Brain FDG-PET Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised anomaly detection using deep learning models is a popular computer-aided diagnosis approach because it does not need annotated data and is not restricted to the … |
Ravi Hassanaly; Simona Bottani; Benoît Sauty; O. Colliot; N. Burgos; | Medical Imaging | 2023-04-03 |
| 473 | Mutual Information Based Anomaly Detection of Monitoring Data with Attention Mechanism and Residual Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
XIAOMING LEI et. al. | Mechanical Systems and Signal Processing | |
| 474 | Energy Grid Management System with Anomaly Detection and Q-learning Decision Modules Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jia-Hao Syu; Gautam Srivastava; M. Fojcik; Rafał Cupek; Chun-Wei Lin; | Comput. Electr. Eng. | 2023-04-01 |
| 475 | Extension of LoRa Coverage and Integration of An Unsupervised Anomaly Detection Algorithm in An IoT Water Quality Monitoring System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: High cost, long-range communication, and anomaly detection issues are associated with IoT systems in water quality monitoring. Therefore, this work proposes a prototype for a … |
Armando Daniel Blanco Jáquez; María T. Alarcon Herrera; A. Celestino; Efraín Neri Ramírez; Diego Armando Martínez Cruz; | Water | 2023-04-01 |
| 476 | Application of Machine Learning Algorithms for The Validation of A New CoAP-IoT Anomaly Detection Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the rise in smart devices, the Internet of Things (IoT) has been established as one of the preferred emerging platforms to fulfil their need for simple interconnections. The … |
Applied Sciences | 2023-04-01 | |
| 477 | Fault and Anomaly Detection in District Heating Substations: A Survey on Methodology and Data Sets Related Papers Related Patents Related Grants Related Venues Related Experts View |
MARTIN NEUMAYER et. al. | Energy | 2023-04-01 |
| 478 | Noise-based Self-supervised Anomaly Detection in Washing Machines Using A Deep Neural Network with Operational Information Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yusun Shul; Wonjun Yi; Jihoon Choi; D. Kang; Jung-Woo Choi; | Mechanical Systems and Signal Processing | 2023-04-01 |
| 479 | A Multivariate Time Series Anomaly Detection Method Based on Clustered Particle Swarm Optimization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the advent of 5G and the integration of sensors, sensor nodes need to collect data from multiple sources simultaneously.Traditional anomaly detection methods for single … |
R. Gao; YR Ding; Yang Wang; | Journal of Physics: Conference Series | 2023-04-01 |
| 480 | Real-Time AI-Based Anomaly Detection and Classification in Power Electronics Dominated Grids Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Real-time anomaly detection system (ADS) and anomaly classification system (ACS) techniques are becoming a crucial need for future power electronic dominated grid (PEDG). … |
Matthew Baker; Amin Y. Fard; Hassan Althuwaini; M. Shadmand; | IEEE Journal of Emerging and Selected Topics in Industrial … | 2023-04-01 |
| 481 | Efficient Driver Anomaly Detection Via Conditional Temporal Proposal and Classification Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Detecting driver inattentive behaviors is crucial for driving safety in a driver monitoring system (DMS). Recent works treat driver distraction detection as a multiclass action … |
Lang Su; Chen Sun; Dongpu Cao; A. Khajepour; | IEEE Transactions on Computational Social Systems | 2023-04-01 |
| 482 | Time-series Anomaly Detection with Stacked Transformer Representations and 1D Convolutional Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jina Kim; H. Kang; Pilsung Kang; | Eng. Appl. Artif. Intell. | 2023-04-01 |
| 483 | AI-Empowered Trajectory Anomaly Detection for Intelligent Transportation Systems: A Hierarchical Federated Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The vigorous development of positioning technology and ubiquitous computing has spawned trajectory big data. By analyzing and processing the trajectory big data in the form of … |
XIAODING WANG et. al. | IEEE Transactions on Intelligent Transportation Systems | 2023-04-01 |
| 484 | FGDAE: A New Machinery Anomaly Detection Method Towards Complex Operating Conditions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
SHEN YAN et. al. | Reliab. Eng. Syst. Saf. | 2023-04-01 |
| 485 | A New Two-phase Intrusion Detection System with Naïve Bayes Machine Learning for Data Classification and Elliptic Envelop Method for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Monika Vishwakarma; N. Kesswani; | Decision Analytics Journal | 2023-04-01 |
| 486 | Photovoltaic Inverter Anomaly Detection Method Based on LSTM Serial Depth Autoencoder Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To ensure the safety of the massive growth of distributed photovoltaic grid-connected inverters and the security of backhaul data in the context of new power systems, research on … |
WEI HU et. al. | Journal of Physics: Conference Series | 2023-04-01 |
| 487 | DC Operating Circuit Anomaly Detection Based on Node Voltage Unsupervised Time Series Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the increase in power system load, the number of switch cabinets increases rapidly, and the accidents caused by DC operating circuits become more and more obvious. Abnormal … |
Shenmin Zhang; Wei Yuan; Ran Yi; Li Chen; | Journal of Physics: Conference Series | 2023-04-01 |
| 488 | Evaluation of Deep Unsupervised Anomaly Detection Methods with A Data-centric Approach for On-line Inspection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Alexander Zeiser; Bekir Özcan; Bas van Stein; T.H.W. Bäck; | Comput. Ind. | 2023-04-01 |
| 489 | Ship Anomalous Behavior Detection Using Clustering and Deep Recurrent Neural Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a … |
Bohan Zhang; K. Hirayama; Hongxiang Ren; Delong Wang; Haijiang Li; | Journal of Marine Science and Engineering | 2023-03-31 |
| 490 | You Only Train Once: Learning A General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a new approach to address the challenge of generalization in hyperspectral anomaly detection (AD). |
ZHAOXU LI et. al. | arxiv-eess.IV | 2023-03-31 |
| 491 | Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose AEGAN-AD, a totally unsupervised approach in which the generator (also an autoencoder) is trained to reconstruct input spectrograms. |
Anbai Jiang; Wei-Qiang Zhang; Yufeng Deng; Pingyi Fan; Jia Liu; | arxiv-cs.SD | 2023-03-31 |
| 492 | Time-series Anomaly Detection Based on Difference Subspace Between Signal Subspaces Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new method for anomaly detection in time-series data by incorporating the concept of difference subspace into the singular spectrum analysis (SSA). |
Takumi Kanai; Naoya Sogi; Atsuto Maki; Kazuhiro Fukui; | arxiv-cs.LG | 2023-03-31 |
| 493 | ISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In the subsequent stage, we apply pixel-level data augmentation techniques to generate corrupted normal images and their corresponding pixel labels. |
Wenping Jin; Fei Guo; Li Zhu; | arxiv-cs.CV | 2023-03-30 |
| 494 | Hard Nominal Example-aware Template Mutual Matching for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, hard-nominal examples are scattered and far apart from most normalities, they are often mistaken for anomalies by existing anomaly detectors. To address this problem, we propose a simple yet efficient method: \textbf{H}ard Nominal \textbf{E}xample-aware \textbf{T}emplate \textbf{M}utual \textbf{M}atching (HETMM). |
Zixuan Chen; Xiaohua Xie; Lingxiao Yang; Jianhuang Lai; | arxiv-cs.CV | 2023-03-28 |
| 495 | Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a disruption prediction method based on anomaly detection that overcomes the drawbacks of unbalanced positive and negative data samples and inaccurately labeled disruption precursor samples. |
XINKUN AI et. al. | arxiv-physics.plasm-ph | 2023-03-27 |
| 496 | EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we focus on computational efficiency and propose a lightweight feature extractor that processes an image in less than a millisecond on a modern GPU. |
Kilian Batzner; Lars Heckler; Rebecca König; | arxiv-cs.CV | 2023-03-25 |
| 497 | The Mass-ive Issue: Anomaly Detection in Jet Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we highlight the main challenge of applying anomaly detection to jet physics, where preserving an unbiased estimator of the jet mass remains a critical piece of any model independent search. |
TOBIAS GOLLING et. al. | arxiv-hep-ph | 2023-03-24 |
| 498 | Interpretable Anomaly Detection Via Discrete Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the decision-making of current deep learning approaches is notoriously hard to understand, which often limits their practical applicability. To overcome this limitation, we propose a framework for learning inherently interpretable anomaly detectors from sequential data. |
SIMON LUTZ et. al. | arxiv-cs.LG | 2023-03-24 |
| 499 | Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study aims to improve PCD anomaly detection performance by combining handcrafted PCD descriptions with powerful pre-trained 2D neural networks. |
Yunkang Cao; Xiaohao Xu; Weiming Shen; | arxiv-cs.CV | 2023-03-23 |
| 500 | Confidence-Aware and Self-Supervised Image Anomaly Localisation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we discuss an improved self-supervised single-class training strategy that supports the approximation of probabilistic inference with loosen feature locality constraints. |
Johanna P. Müller; Matthew Baugh; Jeremy Tan; Mischa Dombrowski; Bernhard Kainz; | arxiv-cs.CV | 2023-03-23 |
| 501 | One-Step Detection Paradigm for Hyperspectral Anomaly Detection Via Spectral Deviation Relationship Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, an unsupervised transferred direct detection (TDD) model is proposed, which is optimized directly for the anomaly detection task (one-step paradigm) and has transferability. |
JINGTAO LI et. al. | arxiv-cs.CV | 2023-03-22 |
| 502 | Failure-tolerant Distributed Learning for Anomaly Detection in Wireless Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: When such failures arise in wireless communications networks, important services that they use/provide (like anomaly detection) can be left inoperable and can result in a cascade of security problems. In this paper, we present a novel method to address these risks by combining both flat- and star-topologies, combining the performance and reliability benefits of both. |
Marc Katzef; Andrew C. Cullen; Tansu Alpcan; Christopher Leckie; Justin Kopacz; | arxiv-cs.LG | 2023-03-22 |
| 503 | TSI-GAN: Unsupervised Time Series Anomaly Detection Using Convolutional Cycle-Consistent Generative Adversarial Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes TSI-GAN, an unsupervised anomaly detection model for time-series that can learn complex temporal patterns automatically and generalize well, i.e., no need for choosing dataset-specific parameters, making statistical assumptions about underlying data, or changing model architectures. |
Shyam Sundar Saravanan; Tie Luo; Mao Van Ngo; | arxiv-cs.LG | 2023-03-22 |
| 504 | Focus or Not: A Baseline for Anomaly Event Detection On The Open Public Places with Satellite Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel satellite imagery dataset(AED-RS) for detecting anomaly events on the open public places. |
Yongjin Jeon; Youngtack Oh; Doyoung Jeong; Hyunguk Choi; Junsik Kim; | arxiv-cs.CV | 2023-03-21 |
| 505 | Defect Detection Approaches Based on Simulated Reference Image Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Among these defect detection methods are classic computer vision applied on difference-image, supervised deep-learning (DL) based on human labels, and unsupervised DL which is trained on feature-level patterns of normal reference images. We show in this study how to incorporate correctly the simulated reference image for these defect and anomaly detection applications. |
Nati Ofir; Yotam Ben Shoshan; Ran Badanes; Boris Sherman; | arxiv-cs.CV | 2023-03-21 |
| 506 | A Hybrid Security System for Drones Based on ICMetric Technology Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, the number of drones has increased, and drones’ illegal and malicious use has become prevalent. The dangerous and wasteful effects are substantial, and the probability … |
Khattab M Ali Alheeti; Fawaz Khaled Alarfaj; Mohammed Alreshoodi; Naif Almusallam; Duaa Al Dosary; | PloS one | 2023-03-21 |
| 507 | Hyperspectral Anomaly Detection Based on Regularized Background Abundance Tensor Decomposition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The low spatial resolution of hyperspectral images means that existing mixed pixels rely heavily on spectral information, making it difficult to differentiate between the target … |
WENTING SHANG et. al. | Remote. Sens. | 2023-03-20 |
| 508 | Fusion Visual Saliency with Dual-spectral Saliency of Anomaly Detection for Hyperspectral Herbal Oral Liquid Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Chinese herbal oral liquid can leach a variety of effective ingredients from herbs and has become a major drug for clinical application. However, it is easy to produce or … |
ATING YIN et. al. | Symposium on Novel Photoelectronic Detection Technology and … | 2023-03-20 |
| 509 | GADFormer: An Attention-based Model for Group Anomaly Detection on Trajectories Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, we introduce with this paper GADFormer, a GAD specific BERT architecture, capable to perform attention-based Group Anomaly Detection on trajectories in an unsupervised and semi-supervised setting. |
Andreas Lohrer; Darpan Malik; Peer Kröger; | arxiv-cs.LG | 2023-03-17 |
| 510 | Anomaly Detection Using Spatial and Temporal Information in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, we propose STADN, a novel Anomaly Detection Network Using Spatial and Temporal Information. |
Zhiwen Tian; Ming Zhuo; Leyuan Liu; Junyi Chen; Shijie Zhou; | Scientific reports | 2023-03-16 |
| 511 | A Bi-LSTM Autoencoder Framework for Anomaly Detection — A Case Study of A Wind Power Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents a novel framework for time series anomaly detection using a combination of Bidirectional Long Short Term Memory (Bi-LSTM) architecture and Autoencoder. |
Ahmed Shoyeb Raihan; Imtiaz Ahmed; | arxiv-cs.LG | 2023-03-16 |
| 512 | Towards Phytoplankton Parasite Detection Using Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose an unsupervised anomaly detection system based on the similarity of the original and autoencoder-reconstructed samples. |
SIMON BILIK et. al. | arxiv-cs.CV | 2023-03-15 |
| 513 | DiffusionAD: Denoising Diffusion for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a new pipeline, DiffusionAD, to anomaly detection. |
Hui Zhang; Zheng Wang; Zuxuan Wu; Yu-Gang Jiang; | arxiv-cs.CV | 2023-03-15 |
| 514 | Adversarial Algorithm Unrolling Network for Interpretable Mechanical Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In mechanical anomaly detection, algorithms with higher accuracy, such as those based on artificial neural networks, are frequently constructed as black boxes, resulting in opaque … |
BOTAO AN et. al. | IEEE transactions on neural networks and learning systems | 2023-03-14 |
| 515 | Dual-distribution Discrepancy with Self-supervised Refinement for Anomaly Detection in Medical Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Medical anomaly detection is a crucial yet challenging task aimed at recognizing abnormal images to assist in diagnosis. Due to the high-cost annotations of abnormal images, most … |
Yu Cai; Hao Chen; Xin Yang; Yu Zhou; Kwang-Ting Cheng; | Medical image analysis | 2023-03-13 |
| 516 | Lifelong Learning for Anomaly Detection: New Challenges, Perspectives, and Insights Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, limited efforts are dedicated to building foundations for lifelong anomaly detection, which provides intrinsically different challenges compared to the more widely explored classification setting. In this paper, we face this issue by exploring, motivating, and discussing lifelong anomaly detection, trying to build foundations for its wider adoption. |
Kamil Faber; Roberto Corizzo; Bartlomiej Sniezynski; Nathalie Japkowicz; | arxiv-cs.LG | 2023-03-13 |
| 517 | Network Anomaly Detection Using Federated Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, most prior works have focused on traditional centralized machine learning, making federated machine learning under-explored in network anomaly detection. Therefore, we propose a deep neural network framework that could work on low to mid-end devices detecting network anomalies while checking if a request from a specific IP address is malicious or not. |
William Marfo; Deepak K. Tosh; Shirley V. Moore; | arxiv-cs.LG | 2023-03-13 |
| 518 | Online Payment Fraud: from Anomaly Detection to Risk Management Related Papers Related Patents Related Grants Related Venues Related Experts View |
P. Vanini; Sebastiano Rossi; Ermin Zvizdic; T. Domenig; | Financial Innovation | 2023-03-13 |
| 519 | Spacecraft Anomaly Detection with Attention Temporal Convolution Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an anomaly detection framework for spacecraft multivariate time-series data based on temporal convolution networks (TCNs). |
Liang Liu; Ling Tian; Zhao Kang; Tianqi Wan; | arxiv-cs.LG | 2023-03-13 |
| 520 | Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compare models trained in open-set (unknown abnormal predictions) and closed-set (abnormal predictions known when training) settings; (b) An anomaly-aware training regime that penalizes the model for predicting periodic signals from anomalous videos. |
JEREMY SPETH et. al. | arxiv-cs.CV | 2023-03-11 |
| 521 | Anomaly Detection with Ensemble of Encoder and Decoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel anomaly detection method by modeling the data distribution of normal samples via multiple encoders and decoders. |
Xijuan Sun; Di Wu; Arnaud Zinflou; Benoit Boulet; | arxiv-cs.LG | 2023-03-11 |
| 522 | Anomaly Detection for Blueberry Data Using Sparse Autoencoder-support Vector Machine Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: High-dimensional space includes many subspaces so that anomalies can be hidden in any of them, which leads to obvious difficulties in abnormality detection. Currently, most … |
Dianwen Wei; Jian Zheng; Hongchun Qu; | PeerJ. Computer science | 2023-03-10 |
| 523 | Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel framework, named Global-Local Correspondence Framework (GLCF), for visual anomaly detection with logical constraints. |
HAIMING YAO et. al. | arxiv-cs.CV | 2023-03-10 |
| 524 | Deep Encrypted Traffic Detection: An Anomaly Detection Framework for Encryption Traffic Based on Parallel Automatic Feature Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a framework of encrypted traffic anomaly detection based on parallel automatic feature extraction, called deep encrypted traffic detection (DETD). |
Gang Long; Zhaoxin Zhang; | Computational intelligence and neuroscience | 2023-03-10 |
| 525 | Deep Anomaly Detection on Tennessee Eastman Process Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper provides the first comprehensive evaluation and analysis of modern (deep-learning) unsupervised anomaly detection methods for chemical process data. |
FABIAN HARTUNG et. al. | arxiv-cs.LG | 2023-03-10 |
| 526 | Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple Yet Efficient Framework Based on Masked Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, even with only normal data training, the AEs often reconstruct anomalies well, which depletes their anomaly detection performance. To alleviate this issue, we propose a simple yet efficient framework for video anomaly detection. |
Xiangyu Huang; Caidan Zhao; Chenxing Gao; Lvdong Chen; Zhiqiang Wu; | arxiv-cs.CV | 2023-03-09 |
| 527 | Anomaly Detection Module for Network Traffic Monitoring in Public Institutions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It seems to be a truism to say that we should pay more and more attention to network traffic safety. Such a goal may be achieved with many different approaches. In this paper, we … |
ŁUKASZ WAWROWSKI et. al. | Sensors (Basel, Switzerland) | 2023-03-09 |
| 528 | Understanding The Challenges and Opportunities of Pose-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we analyze and quantify the characteristics of two well-known video anomaly datasets to better understand the difficulties of pose-based anomaly detection. |
Ghazal Alinezhad Noghre; Armin Danesh Pazho; Vinit Katariya; Hamed Tabkhi; | arxiv-cs.CV | 2023-03-09 |
| 529 | Unsupervised Transformer-Based Anomaly Detection in ECG Signals Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and … |
Abrar Alamr; A. Artoli; | Algorithms | 2023-03-09 |
| 530 | Learning Representation for Anomaly Detection of Vehicle Trajectories Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose two novel methods for learning effective and efficient representations for online anomaly detection of vehicle trajectories. |
RUOCHEN JIAO et. al. | arxiv-cs.LG | 2023-03-08 |
| 531 | Region and Spatial Aware Anomaly Detection for Fundus Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Region and Spatial Aware Anomaly Detection (ReSAD) method for fundus images, which obtains local region and long-range spatial information to reduce the false positives in the normal structure. |
Jingqi Niu; Shiwen Dong; Qinji Yu; Kang Dang; Xiaowei Ding; | arxiv-cs.CV | 2023-03-07 |
| 532 | Anomaly Behavior Detection Analysis in Video Surveillance: A Critical Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstract. Anomaly detection is one of the most researched topics in computer vision and machine learning. Manual detection of an oddity in a video costs significant time and … |
Sanjay Roka; M. Diwakar; Prabhishek Singh; Pragya Singh; | Journal of Electronic Imaging | 2023-03-07 |
| 533 | A Study on The Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we implemented deep learning-based anomaly detection methods for breast ultrasound images and validated their effectiveness in detecting abnormal regions. |
CHANGHEE YUN et. al. | Sensors (Basel, Switzerland) | 2023-03-06 |
| 534 | Scalable and Energy Efficient Cluster Based Anomaly Detection Against Denial of Service Attacks in Wireless Sensor Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
M. Premkumar; R. AshokkumarS.; V. Jeevanantham; G. Mohanbabu; S. Anupallavi; | Wireless Personal Communications | 2023-03-06 |
| 535 | A VHetNet-Enabled Asynchronous Federated Learning-Based Anomaly Detection Framework for Ubiquitous IoT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel VHetNet-enabled asynchronous federated learning (AFL) framework to enable decentralized UAVs to collaboratively train a global anomaly detection model. |
WEILI WANG et. al. | arxiv-cs.NI | 2023-03-06 |
| 536 | TinyAD: Memory-efficient Anomaly Detection for Time Series Data in Industrial IoT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To alleviate the memory constraints of MCUs, we propose a novel framework named Tiny Anomaly Detection (TinyAD) to efficiently facilitate onboard inference of CNNs for real-time anomaly detection. |
Yuting Sun; Tong Chen; Quoc Viet Hung Nguyen; Hongzhi Yin; | arxiv-cs.LG | 2023-03-06 |
| 537 | Achieving Counterfactual Fairness for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a counterfactually fair anomaly detection (CFAD) framework which consists of two phases, counterfactual data generation and fair anomaly detection. |
Xiao Han; Lu Zhang; Yongkai Wu; Shuhan Yuan; | arxiv-cs.LG | 2023-03-03 |
| 538 | CADeSH: Collaborative Anomaly Detection for Smart Homes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For this reason, anomaly-based intrusion detection systems tend to suffer from a high false positive rate (FPR). To overcome this, we propose a two-step collaborative anomaly detection method which first uses an autoencoder to differentiate frequent (`benign’) and infrequent (possibly `malicious’) traffic flows. |
Yair Meidan; Dan Avraham; Hanan Libhaber; Asaf Shabtai; | arxiv-cs.LG | 2023-03-02 |
| 539 | Spatio-temporal Based Video Anomaly Detection Using Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
R. Chaurasia; U. C. Jaiswal; | International Journal of Information Technology | 2023-03-01 |
| 540 | RePAD2: Real-Time, Lightweight, and Adaptive Anomaly Detection for Open-Ended Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, they might exhaust system resources when they are applied to open-ended time series for a long time. To address this issue, in this paper we propose RePAD2, a lightweight real-time anomaly detection approach for open-ended time series by improving its predecessor RePAD, which is one of the state-of-the-art anomaly detection approaches. |
Ming-Chang Lee; Jia-Chun Lin; | arxiv-cs.LG | 2023-03-01 |
| 541 | Unsupervised Image Anomaly Detection and Segmentation Based on Pretrained Feature Mapping IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Image anomaly detection and segmentation are important for the development of automatic product quality inspection in intelligent manufacturing. Because the normal data can be … |
Qian Wan; Liang Gao; Xinyu Li; Long Wen; | IEEE Transactions on Industrial Informatics | 2023-03-01 |
| 542 | Anomaly Detection in Laser Powder Bed Fusion Using Machine Learning: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View |
TAYYABA SAHAR et. al. | Results in Engineering | 2023-03-01 |
| 543 | Deep Learning Based Energy Efficient Optimal RMC-CNN Model for Secured Data Transmission and Anomaly Detection in Industrial IOT Related Papers Related Patents Related Grants Related Venues Related Experts View |
K. Sakthidasan Sankaran; Bong-Hyun Kim; | Sustainable Energy Technologies and Assessments | 2023-03-01 |
| 544 | Multimodal Industrial Anomaly Detection Via Hybrid Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: 2D-based Industrial Anomaly Detection has been widely discussed, however, multimodal industrial anomaly detection based on 3D point clouds and RGB images still has many untouched … |
YUE WANG et. al. | arxiv-cs.CV | 2023-03-01 |
| 545 | Employing A Hybrid Model Based on Texture-biased Convolutional Neural Networks and Edge-biased Vision Transformers for Anomaly Detection of Signal Bonds IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstract. The railway system of Japan plays a vital role in the national transportation network. A key issue in public transport safety is anomaly detection in railways. Lately, … |
Takuro Hoshi; Seiya Shibayama; Xiaonan Jiang; | Journal of Electronic Imaging | 2023-03-01 |
| 546 | First-shot Anomaly Sound Detection for Machine Condition Monitoring: A Domain Generalization Baseline Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To show benchmark performance for First-shot ASD, this paper proposes an anomaly sound detection system that works on the domain generalization task in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Technique while complying with the First-shot requirements introduced in the DCASE 2023 Challenge Task 2 (DCASE2023T2). |
Noboru Harada; Daisuke Niizumi; Yasunori Ohishi; Daiki Takeuchi; Masahiro Yasuda; | arxiv-eess.AS | 2023-03-01 |
| 547 | Semi-supervised Multivariate Time Series Anomaly Detection for Wind Turbines Using Generator SCADA Data Related Papers Related Patents Related Grants Related Venues Related Experts View |
MINGLEI ZHENG et. al. | Reliab. Eng. Syst. Saf. | 2023-03-01 |
| 548 | An Innovative Deep Anomaly Detection of Building Energy Consumption Using Energy Time-series Images IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
A. COPIACO et. al. | Eng. Appl. Artif. Intell. | 2023-03-01 |
| 549 | Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Interestingly, apart from the remarkable image generation abilities of diffusion models, we observed that diffusion models can dissolve image details for a given image, resulting in generalized feature representations. We hereby propose DIA, dissolving is amplifying, that amplifies fine-grained image features by contrasting an image against its feature dissolved counterpart. |
Jian Shi; Pengyi Zhang; Ni Zhang; Hakim Ghazzai; Yehia Massoud; | arxiv-cs.CV | 2023-02-28 |
| 550 | Unsupervised Anomaly Detection for Posteroanterior Chest X-rays Using Multiresolution Patch-based Self-supervised Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The demand for anomaly detection, which involves the identification of abnormal samples, has continued to increase in various domains. In particular, with increases in the data … |
Minki Kim; Ki-Ryum Moon; Byoung-Dai Lee; | Scientific reports | 2023-02-28 |
| 551 | Self-supervised Learning for Textured Surface Anomaly Detection and Localization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming at the problems of insufficient labeled samples and high missed detection rate in common textured surface anomaly detection, the paper designs a self-supervised learning … |
Fei Wang; Fanyong Cheng; Mingyang Zhang; Hong Zhang; | International Conference on Mechatronics Engineering and … | 2023-02-28 |
| 552 | Brain Subtle Anomaly Detection Based on Auto-encoders Latent Space Analysis : Application to De Novo Parkinson Patients Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we design two alternative detection criteria. |
NICOLAS PINON et. al. | arxiv-eess.IV | 2023-02-27 |
| 553 | Combining Autoencoder with Clustering Analysis for Anomaly Detection in Radiotherapy Plans Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To develop an unsupervised anomaly detection method to identify suspicious error-prone treatment plans in radiotherapy. A total of 577 treatment plans of breast cancer patients … |
PENG HUANG et. al. | Quantitative imaging in medicine and surgery | 2023-02-24 |
| 554 | Deep Graph Stream SVDD: Anomaly Detection in Cyber-Physical Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address them, we propose a new approach called deep graph stream support vector data description (SVDD) for anomaly detection. |
Ehtesamul Azim; Dongjie Wang; Yanjie Fu; | arxiv-cs.LG | 2023-02-24 |
| 555 | Hyperspectral Image Anomaly Detection Based on Auto Encoder Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The reason for the existence of small targets and sub-pixel targets in hyperspectral images is that the low spatial resolution leads to the phenomenon of mixed pixels, which makes … |
Guanzhe Li; Lingda Wu; Hongxing Hao; | Fourth International Conference on Geoscience and Remote … | 2023-02-23 |
| 556 | Set Features for Fine-grained Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, such approaches do not extend to scenarios where the anomalies are expressed by an unusual combination of normal elements. In this paper, we overcome this limitation by proposing set features that model each sample by the distribution its elements. |
Niv Cohen; Issar Tzachor; Yedid Hoshen; | arxiv-cs.CV | 2023-02-23 |
| 557 | Explainable Contextual Anomaly Detection Using Quantile Regression Forests Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we develop connections between dependency-based traditional anomaly detection methods and contextual anomaly detection methods. |
Zhong Li; Matthijs van Leeuwen; | arxiv-cs.LG | 2023-02-22 |
| 558 | Quantum Anomaly Detection for Collider Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the use of Quantum Machine Learning (QML) for anomaly detection at the Large Hadron Collider (LHC). |
Sulaiman Alvi; Christian W Bauer; Benjamin Nachman; | Journal of high energy physics : JHEP | 2023-02-22 |
| 559 | An Intelligent Anomaly Detection Approach for Accurate and Reliable Weather Forecasting at IoT Edges: A Case Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Industrialization and rapid urbanization in almost every country adversely affect many of our environmental values, such as our core ecosystem, regional climate differences and … |
Şükrü Mustafa Kaya; Buket İşler; Adnan M Abu-Mahfouz; Jawad Rasheed; Abdulaziz AlShammari; | Sensors (Basel, Switzerland) | 2023-02-22 |
| 560 | Two-stream Decoder Feature Normality Estimating Network for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, these approaches are not explicitly optimized for distinguishable anomalies. To address these problems, we propose a two-stream decoder network (TSDN), designed to learn both normal and abnormal features. |
Chaewon Park; Minhyeok Lee; Suhwan Cho; Donghyeong Kim; Sangyoun Lee; | arxiv-cs.CV | 2023-02-20 |
| 561 | Unsupervised Anomaly Detection with Generative Adversarial Networks in Mammography Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Breast cancer is a common cancer among women, and screening mammography is the primary tool for diagnosing this condition. Recent advancements in deep-learning technologies have … |
Seungju Park; Kyung Hwa Lee; Beomseok Ko; Namkug Kim; | Scientific reports | 2023-02-20 |
| 562 | An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes and evaluates an end-to-end adaptable and configurable anomaly detection system that uses the Intern |