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    • MoLiNet: a local and global information interactive fusion network for improving multi-classification of pathological image artifacts

    • In the field of pathological image artifact classification, researchers have proposed the MoLiNet network, which effectively distinguishes similar artifacts and reduces computational resource consumption.
    • Vol. 30, Issue 11, Pages: 3680-3693(2025)   

      Received:21 November 2024

      Revised:2025-03-14

      Accepted:24 March 2025

      Published:16 November 2025

    • DOI: 10.11834/jig.240691     

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  • Ding W L, Deng R R, Xu L F, Wang C N, Zhu X Q and Zheng K. 2025. MoLiNet: a local and global information interactive fusion network for improving multi-classification of pathological image artifacts. Journal of Image and Graphics, 30(11):3680-3693 DOI: 10.11834/jig.240691.
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相关作者

Wang Teng 淮阴工学院计算机与软件工程学院;江苏省可信固件与智能软件重点实验室
Gao Shangbing 淮阴工学院计算机与软件工程学院;江苏省可信固件与智能软件重点实验室
Ren Gang 东南大学交通学院
Shen Tianshu 山东财经大学计算机与人工智能学院;山东省数字经济轻量智算与可视化重点实验室
Chi Jing 山东财经大学计算机与人工智能学院;山东省数字经济轻量智算与可视化重点实验室
Wang Yanbing 山东财经大学计算机与人工智能学院;山东省数字经济轻量智算与可视化重点实验室
Lei Yanlei 山东财经大学计算机与人工智能学院;山东省数字经济轻量智算与可视化重点实验室
Xu Ming 山东财经大学计算机与人工智能学院;山东省数字经济轻量智算与可视化重点实验室

相关机构

College of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian
Key Laboratory of Trusted Firmware and Intelligent Software of Jiangsu Province, Huaian
School of Transportation, Southeast University
School of Computer and Artificial Intelligence, Shandong University of Finance and Economics, Ji’nan
Shandong Key Laboratory of Lightweight Intelligent Computing and Visualization for Digital Economy, Ji’nan
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