Anomaly Detection
Anomaly detection focuses on identifying unusual patterns or deviations from expected behavior within data, aiming to improve system reliability and safety across diverse applications. Current research emphasizes unsupervised and self-supervised learning approaches, employing architectures like autoencoders, transformers, and graph neural networks, often incorporating techniques such as Bayesian inference and metric learning to enhance robustness and interpretability. The field's significance stems from its broad applicability, ranging from fraud detection and medical diagnosis to industrial process monitoring and network security, with ongoing efforts to develop more efficient, accurate, and explainable methods.
1129papers
Papers - Page 48
March 16, 2023
March 15, 2023
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection
Hui Zhang, Zheng Wang, Zuxuan Wu, Yu-Gang JiangWireless Sensor Networks anomaly detection using Machine Learning: A Survey
Ahsnaul Haque, Md Naseef-Ur-Rahman Chowdhury, Hamdy Soliman, Mohammad Sahinur Hossen, Tanjim Fatima, Imtiaz AhmedReversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection
Cosmin I Bercea, Benedikt Wiestler, Daniel Rueckert, Julia A Schnabel
March 11, 2023
March 9, 2023
Understanding the Challenges and Opportunities of Pose-based Anomaly Detection
Ghazal Alinezhad Noghre, Armin Danesh Pazho, Vinit Katariya, Hamed TabkhiAutomated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier
Sonja Grönroos, Maurizio Pierini, Nadezda ChernyavskayaLearning Representation for Anomaly Detection of Vehicle Trajectories
Ruochen Jiao, Juyang Bai, Xiangguo Liu, Takami Sato, Xiaowei Yuan, Qi Alfred Chen, Qi Zhu
March 7, 2023
Region and Spatial Aware Anomaly Detection for Fundus Images
Jingqi Niu, Shiwen Dong, Qinji Yu, Kang Dang, Xiaowei DingFast and Multi-aspect Mining of Complex Time-stamped Event Streams
Kota Nakamura, Yasuko Matsubara, Koki Kawabata, Yuhei Umeda, Yuichiro Wada, Yasushi SakuraiTinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT
Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin
March 6, 2023
March 4, 2023
March 2, 2023
March 1, 2023
Implementing Active Learning in Cybersecurity: Detecting Anomalies in Redacted Emails
Mu-Huan Chung, Lu Wang, Sharon Li, Yuhong Yang, Calvin Giang, Khilan Jerath, Abhay Raman, David Lie, Mark ChignellMultimodal Industrial Anomaly Detection via Hybrid Fusion
Yue Wang, Jinlong Peng, Jiangning Zhang, Ran Yi, Yabiao Wang, Chengjie WangFirst-shot anomaly sound detection for machine condition monitoring: A domain generalization baseline
Noboru Harada, Daisuke Niizumi, Yasunori Ohishi, Daiki Takeuchi, Masahiro Yasuda