无线电工程2026，Vol.56Issue(2)：319-325,7.DOI:10.3969/j.issn.1003-3106.2026.02.014
面向无人机载平台的轻量级小目标检测算法
Lightweight Small Target Detection Algorithm for Unmanned Aerial Vehicle-borne Platforms
周侃 1刘恒松 2高学攀 3温博 2张刚 2任志国2
作者信息
- 1. 中国电子科技集团公司第五十四研究所,河北 石家庄 050081
- 2. 中国电子科技集团公司第五十四研究所,河北 石家庄 050081||河北省智能化信息感知与处理重点实验室,河北 石家庄 050081
- 3. 中国电子科技集团公司第五十四研究所,河北 石家庄 050081||河北省智能化信息感知与处理重点实验室,河北 石家庄 050081||天津大学智能与计算学部,天津 300350
- 折叠
摘要
Abstract
To address the challenge of limited detection accuracy for small targets in aerial imagery,a lightweight detection framework oriented to unmanned aerial vehicle platforms is designed.Specific improvements are as follows:a high-resolution detection head is added to retain fine-grained feature information;the traditional loss function is replaced by an Efficient Intersection over Union(EIOU)loss function to optimize the efficiency of parameter update;and a dynamic sparse attention module is constructed to enhance feature selection capability while reducing computational complexity.Comparative tests conducted on the VisDrone2019 benchmark dataset show that the improved architecture achieves a significant improvement in mean Average Precision(mAP)metrics compared with the original YOLOv5s,with mAP@EIOU=0.5(mAP50)increased by 8.9%.Ablation study shows that each component significantly improved the detection accuracy and inference efficiency for all categories of targets.The optimized framework maintains the lightweight property of the model,and real-time processing performance of 42 Frames Per Second(FPS)is achieved,thus effectively solving the problem of small target recognition in aerial photography scenarios.关键词
无人机/小目标检测/YOLOv5s/轻量级Key words
unmanned aerial vehicle/small target detection/YOLOv5s/lightweight分类
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周侃,刘恒松,高学攀,温博,张刚,任志国..面向无人机载平台的轻量级小目标检测算法[J].无线电工程,2026,56(2):319-325,7.
