Prototypical Residual Networks for Anomaly Detection and Localization
Author:
Affiliation:
1. School of CS, Fudan University,Shanghai Key Lab of Intell. Info. Processing
2. School of Computer Science, Zhejiang University of Technology
Funder
NSFC
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10204570.pdf?arnumber=10204570
Reference70 articles.
1. Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection
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5. Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection
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