计算机工程与应用2024，Vol.60Issue(17)：167-178,12.DOI:10.3778/j.issn.1002-8331.2402-0230
面向无人机航拍小目标检测的轻量级YOLOv8检测算法
Lightweight YOLOv8 Detection Algorithm for Small Object Detection in UAV Aerial Photography
摘要
Abstract
To address the problems of difficult feature extraction and small targets being overwhelmed by noise in com-plex scenes for target detection in unmanned aerial vehicle(UAV)images,this paper proposes an UAV target detection algorithm called SC-YOLO based on YOLOv8s.Firstly,to learn positional details of regions of interest,a self-position module(SPM)attention based on coordinate attention(CA)is presented.Secondly,to mitigate the impact caused by chan-nel compression of the Carafe upsampling operator,a Carafe enhancer module(CEM)is proposed.Finally,by analyzing the relationship between the gradient gain function and the size of targets in the dataset,this paper enables WIoU_v3 to focus more on the general quality anchor boxes for medium and small targets.This is validated on the VisDrone2019 dataset,where it is found that WIoU_v3 can better target the parameter setting range for general quality anchor boxes of medium and small targets.The improved YOLOv8s algorithm achieves a mean average precision(mAP)of 43.1%on the VisDrone2019 validation set and an mAP of 34.8%on the test set,demonstrating superior detection performance among algorithms of similar scale in recent years.The improved algorithm only adds 1.1×106 in terms of the number of parame-ters and increases the floating point operations(FLOPs)by 1.5 GFLOPs,yet it achieves a 2.0 and 2.1 percentage points in-crease in detection accuracy on the validation and test sets,respectively.On the Tinyperson dataset,the detection accuracy is increased by 1.4 percentage points.关键词
YOLOv8/Carafe/SGE注意力机制/坐标注意力机制/WIoUKey words
YOLOv8/Carafe/SGE attention mechanism/coordinate attention mechanism/WIoU分类
信息技术与安全科学引用本文复制引用
李岩超,史卫亚,冯灿..面向无人机航拍小目标检测的轻量级YOLOv8检测算法[J].计算机工程与应用,2024,60(17):167-178,12.基金项目
国家自然科学基金(62006071) （62006071）
河南省科技攻关项目(232103810086) （232103810086）
河南工业大学粮食信息处理中心开放基金(KFJJ2023010). （KFJJ2023010）
