Vehicle Target Recognition of Large-scale SAR Images Based on YOLOv5
LI Qing
TIAN Tian
TIAN Jinwen
Abstract：Vehicle target recognition in SAR image is a challenging frontier research field.A vehicle target recognition method in large-scale SAR image based on YOLOv5 is proposed.Taking the convolutional neural network YOLOv5 as the basic model of ve-hicle target recognition in large-scale SAR image,the transfer learning method is used to obtain the initial parameters of the model,which effectively reduces the number of training samples and improves the convergence speed of the model.In order to test the per-formance of the algorithm,a large-scale SAR image dataset containing vehicle targets is constructed.Simulation experiments are carried out on this dataset and compared with some classical deep learning networks.The experimental results show that the pro-posed vehicle target recognition algorithm in large-scale SAR image has higher recognition accuracy and faster speed.
Keywords：SAR imagesvehicle target recognitionconvolutional neural network(CNN)transfer learningYOLOv5
Publication Date：2023-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 2852-2858 )