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Bridge bolt defect identification method based on improved YOLOv5s
更新时间：2025-05-26

    • Bridge bolt defect identification method based on improved YOLOv5s

    • “In the field of bridge bolt defect recognition, researchers have proposed a recognition method based on improved YOLOv5s, with a detection accuracy of 90.8% and an average accuracy of 92.6%, providing a solution for intelligent recognition of bridge bolt defects.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 54, Issue 3, Pages: 749-760(2024)
    • 作者机构：

      1.重庆交通大学 省部共建山区桥梁及隧道工程国家重点实验室， 重庆 400074

      2.重庆交通大学 信息科学与工程学院， 重庆 400074

      3.重庆交通大学 航运与船舶工程学院， 重庆 400074

    • DOI：10.13229/j.cnki.jdxbgxb.20230945    

      CLC： U448.14

    • Received：06 September 2023，

      Published：01 March 2024

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  • ZHANG Hong,ZHU Zhi-wei,HU Tian-yu,et al.Bridge bolt defect identification method based on improved YOLOv5s[J].Journal of Jilin University(Engineering and Technology Edition),2024,54(03):749-760. DOI： 10.13229/j.cnki.jdxbgxb.20230945.

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