改进YOLOv8的无人机搜救小目标检测方法

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DOI:10.16652/j.issn.1004-373x.2025.17.025 引用格式：,,，等.改进YOLOv8的无人机搜救小目标检测方法[J].现代电子技术,2025,48(17):167-175.

关键词：无人机搜救；小目标检测；YOLOv8；特征融合；检测头；注意力机制中图分类号：TN911.73-34；TP391.4 文献标识码：A 文章编号：1004-373X（2025）17-0167-09

nproved YOLOv8basedsmallobject detectionmethol forUAVsearchandrescue

JINSiyu,LIJiacheng,HUANGLan,CHENZhongju,ZHANWei (Collge of Computer Science,Yangtze University,Jingzhou 434023, China)

Abstract:Asmallobject detection model YOLOv8-CFTbasedonimproved YOLOv8 isproposed.It aims to improve the smallobjetdetectionperformance when UAVs performsearchandrescue misions incomplexoutdor environments.This model strivestoenhancefeatureextractioncapabilitiesbyintroducingtheC2F-SWCmodule.Meanwhile,itcombinesFADPN(feature aggregatinanddifusion pyramidnetwork)torealizeeficientfeaturefusion.Further,the TDHmoduleisusedtooptimize the detection head tobalance detectionaccuracyanddetectioneffciency.TheYOLOv8-CFTmodel wastestedonthe UAVsearch andrescuedataset UAVSRD.The YOLOv8-CFTmodel issignificantly beterthanthe benchmark YOLOv8 modelin termsof precision rate,recall rate and mAP,among which mAP @0.5 and mAP@0.5: 0.95 increase by 3.8% and 8.9%,respectively. ExperimentalresultsshowthattheYOLOv8-CFTmodelhasbetersmallobjectdetectioncapabilities inUAVsearchandrescue missions.

Keyword:UAVsearchandrescue;small object detection;YOLOv8;feature fusion;detection head;atention mechan

0 引言

无人机（UAV凭借其操作简便、灵活机动的优势，逐渐成为复杂环境中执行任务的理想工具，广泛应用于农业监控、灾害救援等多个领域-2]。（剩余15403字）