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    • Unsupervised industrial defect detection by integrating knowledge distillation and memory mechanism

    • In the field of intelligent manufacturing, experts have proposed an unsupervised industrial defect detection model that integrates knowledge distillation and memory mechanisms, effectively improving detection accuracy and efficiency.
    • Vol. 30, Issue 3, Pages: 660-671(2025)   

      Received:12 April 2024

      Revised:13 August 2024

      Published:16 March 2025

    • DOI: 10.11834/jig.240202     

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  • Liu Bing, Shi Weifeng, Liu Mingming, Zhou Yong, Liu Peng. 2025. Unsupervised industrial defect detection by integrating knowledge distillation and memory mechanism. Journal of Image and Graphics, 30(03):0660-0671 DOI: 10.11834/jig.240202.
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相关作者

Meng Xiangfu 辽宁工程技术大学电子与信息工程学院
Zhang Zhichao 辽宁工程技术大学电子与信息工程学院
Yu Chunlin 辽宁工程技术大学电子与信息工程学院
Zhang Xiaoyan 辽宁工程技术大学电子与信息工程学院
Qiu Miaobo 中国科学院自动化研究所;中国科学院大学人工智能学院
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Lin Shubo 中国科学院自动化研究所;中国科学院大学人工智能学院
Li Liang 军事医学研究院军事认知与脑科学研究所

相关机构

School of Electronics and Information Engineering, Liaoning Technical University
School of Information Science and Technology, ShanghaiTech University
The Brain Science Center, Beijing Institute of Basic Medical Sciences
School of Artificial Intelligence, University of Chinese Academy of Sciences
Institute of Automation, Chinese Academy of Sciences
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