Deep weakly-supervised anomaly detection

• Main Authors: PANG, Guansong, SHEN, Chunhua, JIN, Huidong, VAN DEN HENGEL, Anton
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Anomaly detection; Anomaly detection methods; Deep learning; Intrusion-Detection; Learn+; Performance; Semi-supervised; Type class; Unlabeled data; Unsupervised method; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8411; https://ink.library.smu.edu.sg/context/sis_research/article/9414/viewcontent/Deep_Weakly_supervised_Anomaly_Detection.pdf
• Institution: Singapore Management University

Recent semi-supervised anomaly detection methods that are trained using small labeled anomaly examples and large unlabeled data (mostly normal data) have shown largely improved performance over unsupervised methods. However, these methods often focus on fitting abnormalities illustrated by the given...