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    • Detecting the defects of bridge cables and tunnel lining via integrating attention and enhanced receptive field

    • In the field of bridge cable and tunnel disease detection, experts have proposed a deep network model based on fusion attention and enhanced receptive field, which effectively improves the accuracy of disease extraction and anti-interference ability.
    • Vol. 30, Issue 2, Pages: 467-484(2025)   

      Received:07 April 2024

      Revised:2024-06-17

      Published:16 February 2025

    • DOI: 10.11834/jig.240191     

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  • Huang Zhihai, Luo Haitao, Guo Bo. 2025. Detecting the defects of bridge cables and tunnel lining via integrating attention and enhanced receptive field. Journal of Image and Graphics, 30(02):0467-0484 DOI: 10.11834/jig.240191.
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相关作者

Wang Weijia 福州大学计算机与大数据学院
Chen Fei 福州大学计算机与大数据学院
Liu Wanling 福州大学计算机与大数据学院;天津大学智能与计算学部
Cheng Hang 福州大学数学与统计学院
Wang Meiqing 福州大学数学与统计学院
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

相关机构

College of Computer and Data Science, Fuzhou University
College of Intelligence and Computing, Tianjin University
School of Mathematics and Statistics, Fuzhou 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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