计算机工程2025，Vol.51Issue(6)：184-192,9.DOI:10.19678/j.issn.1000-3428.0068698
基于改进YOLOv3的航拍小目标检测算法
Small Object Detection Algorithm for Aerial Photography Based on Improved YOLOv3
摘要
Abstract
This study presents an improved You Only Look Once version 3(YOLOv3)algorithm for small object detection,to address problems such as low detection precision for small objects,missed detection,and false detection in the detection process.First,in terms of network structure,the feature extraction capability of the backbone network is improved by using DenseNet-121,with a Densely Connected Network(DenseNet),to replace the original Darknet-53 network as its basic network.Simultaneously,the convolution kernel size is modified to further reduce the loss of feature map information,to enhance the robustness of the detection model against small objects.A fourth feature detection layer with a size of 104×104 pixel is added.Second,the bilinear interpolation method is used to replace the original nearest neighbor interpolation method for upsampling operations,to solve the serious feature loss problem in most detection algorithms.Finally,in terms of the loss function,Generalized Intersection over Union(GIoU)is used instead of Intersection over Union(IoU)to calculate the loss value of the boundary frame,and the Focal Loss function is introduced as the confidence loss function of the boundary frame.Experimental results show that the mean Average Precision(mAP)of the improved algorithm on the VisDrone2019 dataset is 63.3％,which is 13.2 percentage points higher than that of the original YOLOv3 detection model,and 52 frame/s on a GTX 1080 Ti device.The improved algorithm has good detection performance for small objects.关键词
小目标检测/YOLOv3/密集连接网络/损失函数/广义交并比Key words
small object detection/You Only Look Once version 3(YOLOv3)/Densely Connected Network(DenseNet)/loss function/Generalized Intersection over Union(GIoU)分类
信息技术与安全科学引用本文复制引用
奚琦,王明杰,魏敬和,赵伟..基于改进YOLOv3的航拍小目标检测算法[J].计算机工程,2025,51(6):184-192,9.基金项目
国家自然科学基金面上项目(62174150) （62174150）
国家自然科学基金青年科学基金项目(62204233) （62204233）
江苏省自然科学基金面上项目(BK20211041,BK20211040) （BK20211041,BK20211040）
江苏省产业前瞻与关键核心技术重点项目(BE2021003-1) （BE2021003-1）
江苏省产业前瞻与关键核心技术项目(BE2023005-1). （BE2023005-1）
