Memory-Guided Hierarchical Feature Reconstruction for Multi-class Unsupervised Anomaly Detection

Kai Huang; Shubo Zhou; Weiyu Hu; Yongbin Gao; Feng Pan; Xueqin Jiang

doi:10.1007/978-981-96-4276-2_16

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Memory-Guided Hierarchical Feature Reconstruction for Multi-class Unsupervised Anomaly Detection

Kai Huang Shubo Zhou Weiyu Hu Yongbin Gao Feng Pan Xueqin Jiang

Year: 2025 Communications in computer and information science Pages: 228-241 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-96-4276-2_16

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Keywords:

Class (philosophy) Computer science Anomaly detection Pattern recognition (psychology) Feature (linguistics) Artificial intelligence Anomaly (physics) Physics

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Smart Grid Security and Resilience

Physical Sciences → Engineering → Control and Systems Engineering

Memory-Guided Hierarchical Feature Reconstruction for Multi-class Unsupervised Anomaly Detection

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