Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection

Haiming Yao; Wei Luo; Yunkang Cao; Yiheng Zhang; Wenyong Yu; Weiming Shen

doi:10.1109/tsmc.2025.3595539

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Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection

Haiming Yao Wei Luo Yunkang Cao Yiheng Zhang Wenyong Yu Weiming Shen

Year: 2025 Journal: IEEE Transactions on Systems Man and Cybernetics Systems Vol: 55 (10)Pages: 7510-7525 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tsmc.2025.3595539

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Keywords:

Zero (linguistics) Anomaly detection Regression Anomaly (physics) Texture (cosmology) Artificial intelligence Shot (pellet) Pattern recognition (psychology) Mathematics Computer science Statistics Physics Image (mathematics) Materials science Condensed matter physics

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Industrial Vision Systems and Defect Detection

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Textile materials and evaluations

Physical Sciences → Materials Science → Polymers and Plastics

Generative Adversarial Networks and Image Synthesis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection

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