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Pavement distress identification method based on improved simAM-YOLOv8
更新时间：2026-01-28

    • Pavement distress identification method based on improved simAM-YOLOv8

    • “In the field of automated detection of road conditions, researchers have proposed the simAM-YOLOv8 algorithm. In response to the problems of multimodal road surface disease data and low recognition accuracy, the improved algorithm has improved the overall recognition accuracy of different types of road surface diseases by 15.3% and the recall rate by 13.1%.”
    • Journal of Jilin University(Engineering and Technology Edition)   Vol. 56, Issue 1, Pages: 219-230(2026)
    • 作者机构：

      1.同济大学 道路与交通工程教育部重点实验室，上海 201804

      2.河南交通发展研究院有限公司，郑州 450066

    • DOI：10.13229/j.cnki.jdxbgxb.20240586    

      CLC： TP391.4;U495

    • Received：26 May 2024，

      Published：01 January 2026

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  • SHAN Fei,LI Hui,SUN Hao,et al.Pavement distress identification method based on improved simAM-YOLOv8[J].Journal of Jilin University(Engineering and Technology Edition),2026,56(01):219-230. DOI： 10.13229/j.cnki.jdxbgxb.20240586.

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