现代信息科技2024，Vol.8Issue(14)：37-42,48,7.DOI:10.19850/j.cnki.2096-4706.2024.14.008
基于改进YOLOv5s的无人机航拍小目标检测算法研究
Research on Small Target Detection Algorithm for UAV Aerial Photography Based on Improved YOLOv5s
尹泉贺 1原素慧 1朱梦琳 1兰洁1
作者信息
- 1. 华北水利水电大学 信息工程学院,河南 郑州 450046
- 折叠
摘要
Abstract
At present,UAV aerial photography target detection technology has been widely applied in military and civilian fields,but in complex scenes,small targets are dense and prone to false positives and missed detections.For this purpose,this paper proposes a small target detection algorithm for drone aerial photography based on improved YOLOv5s,which replaces two ordinary convolutions with grouped convolutions and decoupled detection heads instead of coupled detection heads.The P5 detection head in the original algorithm is removed,and a new P2 detection head is added to the PANet structure.The simulation results show that the improved algorithm has good detection performance,with mAP50 increased by 9.3%compared to the original algorithm,and can meet the real-time detection requirements of UAV.关键词
无人机航拍/小目标检测/空间池化金字塔/解耦检测头Key words
UAV aerial photography/small target detection/spatial pooling pyramid/decoupled detection head分类
信息技术与安全科学引用本文复制引用
尹泉贺,原素慧,朱梦琳,兰洁..基于改进YOLOv5s的无人机航拍小目标检测算法研究[J].现代信息科技,2024,8(14):37-42,48,7.
