Autoencoders with exponential deviation loss for weakly supervised anomaly detection

Min-Seong Kwon; Yong-Geun Moon; Byungju Lee; Jung-Hoon Noh

doi:10.1016/j.patrec.2023.05.016

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JOURNAL ARTICLE

Autoencoders with exponential deviation loss for weakly supervised anomaly detection

Min-Seong Kwon Yong-Geun Moon Byungju Lee Jung-Hoon Noh

Year: 2023 Journal: Pattern Recognition Letters Vol: 171 Pages: 131-137 Publisher: Elsevier BV

DOI: 10.1016/j.patrec.2023.05.016

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Keywords:

Anomaly detection Autoencoder Anomaly (physics) Pattern recognition (psychology) Computer science Artificial intelligence Exponential function Representation (politics) Data mining Mathematics Artificial neural network

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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

Artificial Immune Systems Applications

Physical Sciences → Engineering → Biomedical Engineering

Autoencoders with exponential deviation loss for weakly supervised anomaly detection

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