Search Results for author: Tongkun Liu

Found 3 papers, 3 papers with code

Component-aware anomaly detection framework for adjustable and logical industrial visual inspection

1 code implementation15 May 2023 Tongkun Liu, Bing Li, Xiao Du, Bingke Jiang, Xiao Jin, Liuyi Jin, Zhuo Zhao

Meanwhile, segmenting a product image into multiple components provides a novel perspective for industrial visual inspection, demonstrating great potential in model customization, noise resistance, and anomaly classification.

Anomaly Classification Anomaly Detection +1

Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detection

1 code implementation26 Oct 2022 Tongkun Liu, Bing Li, Zhuo Zhao, Xiao Du, Bingke Jiang, Leqi Geng

The model with an overly strong generalization capability can even well reconstruct the abnormal regions, making them less distinguishable, while the model with a poor generalization capability can not reconstruct those changeable high-frequency components in the normal regions, which ultimately leads to false positives.

Anomaly Detection Denoising

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