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    • Industrial anomaly detection by combining visual Mamba and patch feature distribution

    • “The latest research proposes an unsupervised industrial anomaly detection model that combines visual Mamba and block feature distribution, effectively improving detection performance and providing a new solution for the field of industrial anomaly detection.”
    • Vol. 30, Issue 10, Pages: 3215-3229(2025)   

      Received：21 October 2024，

      Revised：2025-01-18，

      Published：16 October 2025

    • DOI： 10.11834/jig.240594     

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  • Liu Jianming， Zhuang Weikuan. 2025. Industrial anomaly detection by combining visual Mamba and patch feature distribution. Journal of Image and Graphics， 30(10):3215-3229 DOI： 10.11834/jig.240594.
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Zhuang Weikuan 江西师范大学数字产业学院
Liu Jianming 江西师范大学数字产业学院;江西师范大学计算机信息工程学院
Feng Jun 石家庄铁道大学信息科学与技术学院;石家庄市人工智能重点实验室
Meng Xujing 石家庄铁道大学信息科学与技术学院;石家庄市人工智能重点实验室
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Niu Chaofan 河北圣昊光电科技有限公司
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School of Computer and Information Engineering Jiangxi Normal University
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