Laser Journal, Volume. 45, Issue 8, 92(2024)

Research on workpiece anomaly detection algorithm based on inverse knowledge distillation

ZHANG Xiaoyong1...2, WANG Liming1,2,*, LI Xuan1,2, and HAN Xingcheng12 |Show fewer author(s)
Author Affiliations
  • 1College of Information and Communication Engineering, North University of China, Taiyuan 030051, China
  • 2Shanxi Key Laboratory of Signal Capturing and Processing (North University of China), Taiyuan 030051, China
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    References(14)

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    [4] [4] Liu W, Chang H, Ma B, et al. Diversity-measurable anomaly detection[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023: 12147-12156.

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    [8] [8] Xie H, Xiao Y. Multiresolution Knowledge Distillation and Multi-level Fusion for Defect Detection[C]//International Conference on Green, Pervasive, and Cloud Computing. Cham: Springer International Publishing, 2022: 178-191.

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    [11] [11] Yan H, Liu Z, Chen J, et al. Memory-augmented skipconnected autoencoder for unsupervised anomaly detection of rocket engines with multi-source fusion[J]. ISA transactions, 2023, 133: 53-65.

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    ZHANG Xiaoyong, WANG Liming, LI Xuan, HAN Xingcheng. Research on workpiece anomaly detection algorithm based on inverse knowledge distillation[J]. Laser Journal, 2024, 45(8): 92

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    Paper Information

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    Received: Jan. 5, 2024

    Accepted: Dec. 20, 2024

    Published Online: Dec. 20, 2024

    The Author Email: Liming WANG (wlm@nuc.edu.cn)

    DOI:10.14016/j.cnki.jgzz.2024.08.092

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