基于YOLOv5s的行人与车辆检测算法研究OA
Research on improved pedestrian and vehicle detection algorithm based on YOLOv5s
针对城市交通环境复杂程度高,行人和车辆的检测结果精度偏低的问题.提出了改进的YOLOv5s行人与车辆检测算法.首先,在YOLOv5s加入SK注意力机制,同时选用GSConv模块替换网络中部分卷积模块,用于有效提升检测精度,同时保持网络参数量基本不变;其次,引入ECIOU损失函数,能够加快模型收敛;最后通过选用KITTI数据集来检验改进算法的效果.最终实验结果表明,改进后的YOLOv5s算法,在保证算法参数量基本不变的同时,可将行人与车辆平均检测精…查看全部>>
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 uncha…查看全部>>
朱立忠;邵永斌;杜海洋
沈阳理工大学自动化与电气工程学院,辽宁沈阳 110159沈阳理工大学自动化与电气工程学院,辽宁沈阳 110159沈阳理工大学自动化与电气工程学院,辽宁沈阳 110159
计算机与自动化
YOLOv5s行人车辆检测注意力机制损失函数优化
YOLOv5sPedestrian and vehicle detectionUrban transportationOptimization of loss function
《通信与信息技术》 2024 (3)
98-102,5
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