现代电子技术2025，Vol.48Issue(7)：43-47,5.DOI:10.16652/j.issn.1004-373x.2025.07.007
选择性坐标注意力下红外图像无人机目标检测方法
UAV object detection method for infrared images based on selective coordinate attention
摘要
Abstract
This paper proposes an unmanned aerial vehicle(UAV)object detection method for infrared images based on selective coordinate attention in order to avoid the security risks and privacy violations caused by UAVs.On the basis of the selective coordinate attention mechanism,the asymmetric convolutional kernels are used to capture features of different scales and shapes in different directions.The row and column position information of UAV features is encoded,the weights of different position features are adjusted dynamically,and the feature representations of key regions are strengthened.After inputting multiple infrared images into the YOLOv5 network for training and processing,a selective coordinate attention mechanism is embedded in the backbone network after convolution operation,so as to achieve accurate feature extraction of UAV objects in infrared images.The GIoU is taken as the loss function to optimize the position and size of the prediction box,so as to achieve accurate detection of UAV objects in infrared images.The experimental results show that the method can locate and detect UAV objects of different sizes accurately and quickly,and can maintain high detection accuracy.关键词
坐标注意力机制/特征融合/YOLOv5网络/红外图像/无人机目标/目标检测Key words
coordinate attention mechanism/feature fusion/YOLOv5 network/infrared image/UAV object/object detection分类
电子信息工程引用本文复制引用
吴茜,魏晶鑫,陈中举..选择性坐标注意力下红外图像无人机目标检测方法[J].现代电子技术,2025,48(7):43-47,5.基金项目
中国高校产学研创新基金:新一代信息技术创新项目(2023IT269) （2023IT269）
