现代信息科技2024，Vol.8Issue(1)：94-98,103,6.DOI:10.19850/j.cnki.2096-4706.2024.01.019
基于改进YOLOv5的交通标志小目标检测算法
Traffic Sign Small Target Detection Algorithm Based on Improved YOLOv5
刘振渤 1李慧 1刘桥缘 2胡蓉1
作者信息
- 1. 西华大学,四川 成都 610039
- 2. 四川省公安厅交通警察总队,四川 成都 610000
- 折叠
摘要
Abstract
Aiming at the low detection accuracy of traffic sign small targets and dense targets of traffic signs,an improved YOLOv5s detection model is proposed.It adds ECA attention mechanism to enhance feature information extraction ability of traffic sign small target in Backbone network.Secondly,it adopts SPPCSPC structure to reduce information loss of traffic sign small target.Then,it re-uses BiFPN network to fuse multi-scale feature information to enhance the fusion perception ability.Finally,WIoU is used as the loss function of the model during training to reduce excessive interference of background and improve the accuracy of traffic sign detection.The experimental results show that the accuracy of the improved algorithm is 93.3%,and the mAP value is 92.7%,which is 2.2%and 1.7%higher than before,respectively.关键词
交通标志小目标/YOLOv5s/ECA注意力机制/SPPCSPC模块/WIoU lossKey words
traffic sign small target/YOLOv5s/ECA attention mechanism/SPPCSPC module/WIoU loss分类
信息技术与安全科学引用本文复制引用
刘振渤,李慧,刘桥缘,胡蓉..基于改进YOLOv5的交通标志小目标检测算法[J].现代信息科技,2024,8(1):94-98,103,6.
