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Graph-Attention-Regularized Deep Support Vector Data Description for Semi-Supervised Anomaly Detection: A Case Study in Automotive Quality Control

This paper addresses semi-supervised anomaly detection in settings where only a small subset of normal data can be labeled. Such conditions arise, for example, in industrial quality control of windshield wiper noise, where expert labeling is costly and limited. Our objective is to learn a one-class...

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Auteur principal: Taha J. Alhindi
Format: Artigo
Langue:Inglês
Publié: MDPI AG 2025-12-01
Collection:Mathematics
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Accès en ligne:https://www.mdpi.com/2227-7390/13/23/3876
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