SCGAN: Extract Features From Normal Semantics for Unsupervised Anomaly Detection
Anomaly detection within the realm of industrial products seeks to identify regions of image semantics that deviate from established normal patterns. Given the inherent challenges associated with collecting anomaly samples, we exclusively extract features from normal semantics. Our proposed solution...
Main Authors: | Yang Dai, Lin Zhang, Fu-You Fan, Ya-Juan Wu, Ze-Kuan Zhao |
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Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10345606/ |
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