计算机工程与应用2025，Vol.61Issue(4)：272-281,10.DOI:10.3778/j.issn.1002-8331.2407-0399
改进RT-DETR的航拍小目标检测算法
Improved RT-DETR Algorithm for Aerial Small Object Detection
摘要
Abstract
Aiming to address the issue of missed and false detection of small objects in aerial photography images by existing object detection algorithms,an improved algorithm based on RT-DETR(real-time detection transformer)is proposed.Partial convolution(PConv)is introduced into the backbone network,and a PConvBlock structure is designed.Then,a Basic-Block-PConvBlock module composed of PConvBlocks replaces the original BasicBlock,effectively reducing the number of model parameters.The bidirectional feature pyramid network(BiFPN)structure is adopted to optimize the feature fusion module.The S2 feature is introduced to enhance the detection ability of small objects.The CARAFE upsampling operator is introduced to strengthen the fast fusion of multi-scale features.Experimental results show that the improved model has a 13.9%reduction in parameter number compared to the RT-DETR model,and the mAP0.5 and mAP0.5:0.95 indicators are improved by 2.4 and 1.9 percentage points,respectively on the VisDrone test set.On the TT100K and DOTA datasets,the improved model outperforms the RT-DETR algorithm.The improved model significantly enhances detection accuracy while maintaining a smaller parameter number and computational cost,meeting the real-time detection application require-ments for drone aerial photography images.关键词
小目标检测/轻量化/RT-DETR/部分卷积Key words
small object detection/lightweight/RT-DETR/partial convolution分类
信息技术与安全科学引用本文复制引用
刘思元,高凯,雍龙泉..改进RT-DETR的航拍小目标检测算法[J].计算机工程与应用,2025,61(4):272-281,10.基金项目
陕西省自然科学基础研究计划项目(2024JC-YBMS-014) （2024JC-YBMS-014）
陕西省教育厅青年创新团队项目(23JP024) （23JP024）
陕西理工大学科研项目(SLGNL202409). （SLGNL202409）
