Results 11 to 20 of about 307,816 (329)
A systematic survey: role of deep learning-based image anomaly detection in industrial inspection contexts [PDF]
Frontiers in Robotics and AIIndustrial automation is rapidly evolving, encompassing tasks from initial assembly to final product quality inspection. Accurate anomaly detection is crucial for ensuring the reliability and robustness of automated systems.
Vinita Shukla +3 more
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Research Progress of Video Anomaly Detection Technology [PDF]
Jisuanji kexue yu tansuo, 2022 Video anomaly detection refers to the detection and identification of events that deviate from normal behavior, which has a wide range of applications in surveillance video.
WU Kaijun, HUANG Tao, WANG Dicong, BAI Chenshuai, TAO Xiaomiao
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Multi-Perspective Anomaly Detection [PDF]
Sensors, 2021 Anomaly detection is a critical problem in the manufacturing industry. In many applications, images of objects to be analyzed are captured from multiple perspectives which can be exploited to improve the robustness of anomaly detection. In this work, we build upon the deep support vector data description algorithm and address multi-perspective anomaly ...
Peter Jakob +3 more
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SA-PatchCore: Anomaly Detection in Dataset With Co-Occurrence Relationships Using Self-Attention
IEEE Access, 2023 Various unsupervised anomaly detection methods using deep learning have recently been proposed, and the accuracy of the anomaly detection technique for local anomalies has been improved.
Kengo Ishida +5 more
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Nuclear Physics B, 2022 Anomaly detection algorithms have been proved to be useful in the search of new physics beyond the Standard Model. However, a prerequisite for using an anomaly detection algorithm is that the signal to be sought is indeed anomalous.
Ji-Chong Yang, Yu-Chen Guo, Li-Hua Cai
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Anomaly Detection As-a-Service [PDF]
2019 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 2019 Paper accepted at the Intl. Workshop on Governing Adaptive and Unplanned Systems of Systems (GAUSS)
Mobilio, M +4 more
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Detecting network performance anomalies with contextual anomaly detection [PDF]
2017 IEEE International Workshop on Measurement and Networking (M&N), 2017 Network performance anomalies can be defined as abnormal and significant variations in a network's traffic levels. Being able to detect anomalies is critical for both network operators and end users. However, the accurate detection without raising false alarms can become a challenging task when there is high variance in the traffic.
Dimopoulos, Giorgos +3 more
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Subspace-Based Anomaly Detection for Large-Scale Campus Network Traffic
Journal of Applied Mathematics, 2023 With the continuous development of information technology and the continuous progress of traffic bandwidth, the types and methods of network attacks have become more complex, posing a great threat to the large-scale campus network environment.
Xiaofeng Zhao, Qiubing Wu
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Video anomaly detection using Cross U-Net and cascade sliding window
Journal of King Saud University: Computer and Information Sciences, 2022 As video surveillance exponentially increases, a method that automatically detects abnormal events in video surveillance is essential. Several anomaly detection methods have been proposed to detect abnormal events in video surveillance. Much research has
Yujun Kim +3 more
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Saliencycut: Augmenting Plausible Anomalies for Anomaly Detection
Pattern Recognition, 2023 Anomaly detection under open-set scenario is a challenging task that requires learning discriminative fine-grained features to detect anomalies that were even unseen during training. As a cheap yet effective approach, data augmentation has been widely used to create pseudo anomalies for better training of such models.
Jianan Ye +5 more
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