通信与信息技术Issue(3)：98-102,5.
基于YOLOv5s的行人与车辆检测算法研究
Research on improved pedestrian and vehicle detection algorithm based on YOLOv5s
朱立忠 1邵永斌 1杜海洋1
作者信息
- 1. 沈阳理工大学自动化与电气工程学院,辽宁沈阳 110159
- 折叠
摘要
Abstract
Aiming at the problem of high complexity of urban traffic environment and low accuracy of pedestrian and vehicle de-tection results.An improved YOLOv5s pedestrian and vehicle detection algorithm is proposed.Firstly,the SK attention mechanism is added to YOLOv5s,and the GSConv module is selected to replace some convolutional modules in the network,which is used to effec-tively improve the detection accuracy while keeping the network parameters basically unchanged.Secondly,the ECIOU loss function is introduced,which can accelerate the model convergence.Finally,the KITTI dataset is selected to test the effect of the improved algo-rithm.The final experimental results show that the improved YOLOv5s algorithm can improve the average detection accuracy of pedes-trians and vehicles from 81.2%to 87.3%while ensuring that the number of parameters of the algorithm is basically unchanged,which verifies the effectiveness of this study.关键词
YOLOv5s/行人车辆检测/注意力机制/损失函数优化Key words
YOLOv5s/Pedestrian and vehicle detection/Urban transportation/Optimization of loss function分类
信息技术与安全科学引用本文复制引用
朱立忠,邵永斌,杜海洋..基于YOLOv5s的行人与车辆检测算法研究[J].通信与信息技术,2024,(3):98-102,5.
