基于改进Y0L0v10的轻量化交通流量检测

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中图分类号：TP391.4 文献标识码：A 文章编号：2096-4706（2025）08-0077-06

Abstract：Inorder tosolvetheshortcomingsoftraditional trafficflow statisticsalgorithms inreal-time，stabilityand accuracy，atargetdetectionalgorithmbasedonimprovedYOLOv10algorithm is proposed.TheimprovedYOLOv10algorithm is combined withDepSORTtracking technologytoconstructanew traffcflowstatisticalarchitecture.The traffcscene video oftheactualroadconditioniscollctedtoverifytheaccuracyofthe framework.Theexperimentalresultsshowthatcompared with the originalalgorithm，theaverage accuracyoftheimprovednewalgorithm invehicle detectionis improved by 1 % ，and the statistical accuracy of video traffic flow is improved by 3 . 4 6 %

Keywords： computer vision; traffc flow statistic; YOLO; DeepSORT; intelligent transportatiol

0 引言

在城市化进程持续推进的过程中，城市空间规模呈现出不断增长的态势。（剩余7527字）