Multi-scale Feature Imitation for Unsupervised Anomaly Localization

Chao Hu; Shengxin Lai

doi:10.1007/978-981-97-0855-0_49

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Multi-scale Feature Imitation for Unsupervised Anomaly Localization

Chao Hu Shengxin Lai

Year: 2024 Lecture notes in electrical engineering Pages: 523-534 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-0855-0_49

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Keywords:

Scale (ratio) Imitation Feature (linguistics) Computer science Anomaly (physics) Anomaly detection Artificial intelligence Pattern recognition (psychology) Geography Cartography Psychology Neuroscience Physics

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Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Time Series Analysis and Forecasting

Physical Sciences → Computer Science → Signal Processing

Multi-scale Feature Imitation for Unsupervised Anomaly Localization

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