基于改进YOLOv5s的道路凹坑检测算法  

Road pothole detection algorithm based on improved YOLOv5s

作　　者：甘波 邢伟寅 刘洪义[5] 梁姝 蒲国林[2] 代超 GAN Bo;XING Weiyin;LIU Hongyi;LIANG Shu;PU Guolin;DAI Chao(Sichuan ZhiShiYunTong Technology Co.,Ltd.,Chengdu 610000,China;Dazhou Vocational and Technical College,Dazhou 635000,China;National University(Philippines),Manila 1101,Philippines;Mianyang Polytechnic,Mianyang 621000,China;School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400000,China;Sichuan Intelligent Expressway Technology Co.,Ltd.,Chengdu 610000,China)

机构地区：[1]四川智视运通科技有限公司,四川成都610000 [2]达州职业技术学院,四川达州635000 [3]菲律宾国家大学,菲律宾马尼拉1101 [4]绵阳职业技术学院,四川绵阳621000 [5]重庆交通大学土木工程学院,重庆400000 [6]四川智慧高速科技有限公司,四川成都610000

出　　处：《中国测试》2024年第4期160-165,共6页China Measurement & Test

基　　金：四川省科技计划重点研发项目(2022YFG0206);四川省知识产权专项资金项目(2022-ZS-00156);达州市“同心智库”(TXZK23D17)。

摘　　要：为快速准确识别道路凹坑,研究提出一种基于改进YOLOv5s的道路凹坑检测算法。在YOLOv5s算法的主干网络中结合高效通道注意力机制,提高对凹坑区域的关注度;然后在检测头使用高效解耦头,有利于对凹坑进行准确预测;同时在边框损失函数中增加归一化Wasserstein距离损失,提升对小目标的检测能力。改进后的算法对复杂路况的凹坑检测具有较高的精度,在Pothole Dataset扩展数据集上,mAP和Precision上均超过原算法。将算法用于智慧交通领域,以便能更快地修复道路上严重凹坑。To rapidly and accurately identify road potholes,a detection algorithm based on an improved YOLOv5s has been proposed.The algorithm incorporates an efficient channel attention mechanism into the backbone network of YOLOv5s to enhance focus on pothole areas;it then utilizes efficient decoupled head in the detection head,which is beneficial for accurate pothole prediction;additionally,the bounding box loss function is augmented with normalized Wasserstein distance loss to improve the detection capability for small targets.The improved algorithm demonstrates higher accuracy in pothole detection under complex road conditions,surpassing the original algorithm in both mAP and Precision on the expanded Pothole Dataset.Applying this algorithm in the field of intelligent transportation can facilitate the faster repair of severe potholes on roads.

关 键 词：深度学习 智慧交通 目标检测 YOLOv5s 

分 类 号：TB9[一般工业技术—计量学]