徐州工程学院学报（自然科学版）2025，Vol.40Issue(4)：57-63,7.
基于轻量化YOLOv8s的无人机红外目标检测算法
An Infrared Target Detection Algorithm for UAVs Based on Lightweight YOLOv8s
摘要
Abstract
In response to the challenges of target detection posed by dense,small targets and complex backgrounds in UAV aerial infrared images,this paper presents an improved algorithm named EUAV_YOLOv8s,which is based on YOLOv8.Firstly,the algorithm incorporates the SEGS module to enhance the extraction of contextual semantic information by embedding the Squeeze-and-Excitation(SE)attention mechanism in the C2f module and integrating GhostNet to reduce model size.Secondly,a tiny object detection head has been added and a lightweight decoupled head structure has been designed to reduce model complexity without compromising detection accuracy.Finally,the Wise Intersection over Union(WIoU)loss function has been incorporated to enhance the performance of bounding box regression.Experimental results demonstrate that the improved algorithm achieves an mAP@50％of 83.3％and a detection speed of 373 FPS,significantly surpassing the performance of mainstream algorithms.关键词
YOLOv8s/轻量化/目标检测/无人机/红外图像Key words
YOLOv8s/lightweight/target detection/Unmanned Aerial Vehicles/infrared image分类
信息技术与安全科学引用本文复制引用
HUANG Zedong,JIAO Wenwen,SU Mingxuan,LIU Jinfu..基于轻量化YOLOv8s的无人机红外目标检测算法[J].徐州工程学院学报（自然科学版）,2025,40(4):57-63,7.基金项目
常州市应用基础研究项目(CJ20250007) （CJ20250007）
常州市领军型创新人才项目(CQ2021079) （CQ2021079）
