Self-Supervised Learning for Industrial Image Anomaly Detection by Simulating Anomalous Samples

Abstract Industrial image anomaly detection (AD) is a critical issue that has been investigated in different research areas. Many works have attempted to detect anomalies by simulating anomalous samples. However, how to simulate abnormal samples remains a significant challenge. In this study, a meth...

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מידע ביבליוגרפי

Principais autores:	Mingjing Pei, Ningzhong Liu, Bing Zhao, Han Sun
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Springer 2023-09-01
סדרה:	International Journal of Computational Intelligence Systems
נושאים:	Industrial image anomaly detection Self-supervised learning Data augmentation Deep learning
גישה מקוונת:	https://doi.org/10.1007/s44196-023-00328-0
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!