指挥控制与仿真2025，Vol.47Issue(6)：76-81,6.DOI:10.3969/j.issn.1673-3819.2025.06.011
基于轻量化网络的无人机图像目标识别
Based on lightweight network drone image target recognition
郭靖 1郭杰 2马玉 3王凤山 1蒲海鹏1
作者信息
- 1. 陆军工程大学野战工程学院,江苏 南京 210007
- 2. 东南大学,江苏 南京 211189
- 3. 无锡市委党校,江苏 无锡 214128
- 折叠
摘要
Abstract
In response to the problem of large computational complexity and false detections in target detection by drones.A target recognition method based on lightweight networks has been proposed.Based on the YOLOv5 object detection algo-rithm,the algorithm has been optimized using the FasterNet lightweight network architecture,which reduces the number of network parameters and improves the efficiency of the algorithm.In order to accurately capture and emphasize key informa-tion in the input sequence,and further enhance the performance of the algorithm,a parameter free attention mechanism Si-mAM is introduced.The results indicate that this method is an optimized application of object detection technology,which can better balance the relationship between detection speed and accuracy,and achieve better detection results in unmanned aerial vehicle aerial image detection tasks.关键词
目标检测/YOLOv5/轻量化网络结构/注意力机制Key words
object detection/YOLOv5/lightweight network structure/attention mechanism引用本文复制引用
郭靖,郭杰,马玉,王凤山,蒲海鹏..基于轻量化网络的无人机图像目标识别[J].指挥控制与仿真,2025,47(6):76-81,6.
