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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:2024-08-13

      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

Bai Xuefei 山西大学计算机与信息技术学院
Wang Yuanhui 山西大学计算机与信息技术学院
Xu Wenjie 山西大学计算机与信息技术学院
Jiang Gaoxia 山西大学计算机与信息技术学院
Wang Wenjian 计算智能与中文信息处理教育部重点实验室(山西大学)
Zhang Ke 华北电力大学电子与通信工程系;华北电力大学河北省电力物联网技术重点实验室;电力物联智慧化技术河北省工程研究中心
Sheng Xin 华北电力大学电子与通信工程系
Xiao Yangjie 华北电力大学电子与通信工程系

相关机构

Key Laboratory of Computational Intelligence and Chinese Information Processing (Shanxi University), Ministry of Education
School of Computer and Information Technology, Shanxi University
Hebei Engineering Research Center of Intelligent Technology for Power Internet of Things
Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University
Department of Electronic and Communication Engineering, North China Electric Power University
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