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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:17 June 2024

      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

Yu Lingxiao 南京航空航天大学计算机科学与技术学院
Hao Jie 南京航空航天大学计算机科学与技术学院;软件新技术与产业化协同创新中心
Zuo Liang 南京航空航天大学计算机科学与技术学院
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Liu Jie 辽宁工程技术大学软件学院
Jiang Wentao 辽宁工程技术大学软件学院
Liu Wanjun 辽宁工程技术大学软件学院
Bai Xuefei 山西大学计算机与信息技术学院

相关机构

School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics
Center for Collaborative Innovation in Software Technology and Industrialization
College of Software, Liaoning Technical University
School of Computer and Information Technology, Shanxi University
Key Laboratory of Computational Intelligence and Chinese Information Processing (Shanxi University), Ministry of Education
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