沈阳航空航天大学学报2024，Vol.41Issue(1)：68-75,8.DOI:10.3969/j.issn.2095-1248.2024.01.009
基于改进YOLOv5s的无人机航拍视频中道路异常目标检测算法
Abnormal road objects detection algorithm in UAV aerial videos based on improved YOLOv5s
摘要
Abstract
During the use of UAV for pedestrian and non-motorized vehicle detection in motorway,the problem of low accuracy and poor performance in object detection was found.To solve these prob-lems,a pedestrian and non-motorized vehicle detection algorithm YOLOv5s-P2S was proposed for UAV perspective.Firstly,the neck part of the YOLOv5s model was extended based on the original PAFPN feature fusion scheme,and a detection layer specifically for small object was added.Then,a small object detection head was added to the prediction part to predict the output feature map of the small object detection layer.Finally,the localization loss function of YOLOv5s was modified to SIOU to improve the detection accuracy and regression efficiency of the anchor box.The experimental results showed that compared with the YOLOv5s model,the average accuracy mean mAP50 of YOLOv5s-P2S increased by 0.05,and the parameters only increased by 0.2M.YOLOv5s-P2S can meet the accuracy and real-time requirements of pedestrian and non-motorized vehicle object detection for UAV perspective.关键词
YOLOv5s/道路目标检测/小目标检测层/SIOU/特征融合/无人机航拍视频Key words
YOLOv5s/road object detection/small object detection layer/SIOU/feature fusion/UAV aerial videos分类
信息技术与安全科学引用本文复制引用
赵磊,孙鹏,刘岩松,沈喆..基于改进YOLOv5s的无人机航拍视频中道路异常目标检测算法[J].沈阳航空航天大学学报,2024,41(1):68-75,8.基金项目
国家重点研发计划专项(项目编号:2017YFC0822204) （项目编号:2017YFC0822204）
