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Oct, 2022
用于工业异常检测的非对称师生网络
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection
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Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, Bastian Wandt
TL;DR
该研究提出了一种解决AD领域师生方法存在的问题的新方法——不对称师生网络(AST),通过使用归一化流密度评估作为教师和传统前馈网络作为学生,以检测工业缺陷,并取得了关于图像级异常检测的最新成果。
Abstract
Industrial
defect detection
is commonly addressed with
anomaly detection
(AD) methods where no or only incomplete data of potentially occurring defects is available. This work discovers previously unknown problem
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