北京测绘2023，Vol.37Issue(9)：1232-1236,5.DOI:10.19580/j.cnki.1007-3000.2023.09.006
基于改进YOLOV5模型的嵌入式端航拍图像目标检测
Embedded aerial image object detection based on improved YOLOV5 model
倪立 1黄征 2杨静3
作者信息
- 1. 联合数维(杭州)科技有限公司,浙江杭州 310000
- 2. 杭州市土地勘测设计规划院有限公司,浙江杭州 310000
- 3. 中国水利水电第八工程局有限公司,湖南长沙 410000
- 折叠
摘要
Abstract
As the deep learning-based target detection model becomes more and more mature,it has become an important research direction to deploy the target detection model to aerial unmanned aerial vehicle(UAV).Aiming at the limited computing power and memory of the onboard reasoning equipment of UAV,a structural reparameterized you only look once V5(YOLOV5)aerial target detection model was proposed.Firstly,the feature extraction network of the YOLOV5 model was replaced as the structurally reconfigurable network.Then,the multi-branch YOLOV5 model was trained with the help of the open source data set.Then,the multi-branch network was reparameterized to obtain the single-path network model.The experiment showed that the reasoning speed of the reparametric YOLOV5 model increased by about 3 times,the detection rate increased by 0.03％,the recall rate increased by 0.02％,and the mAP0.5 increased by 1.22.关键词
航拍无人机目标检测/网络模型重参化/YOLOV5模型Key words
aerial photography unmanned aerial vehicle(UAV)target detection/network model reparameterization/you only look once V5(YOLOV5)分类
天文与地球科学引用本文复制引用
倪立,黄征,杨静..基于改进YOLOV5模型的嵌入式端航拍图像目标检测[J].北京测绘,2023,37(9):1232-1236,5.
