信息工程大学学报2023，Vol.24Issue(5)：526-532,7.DOI:10.3969/j.issn.1671-0673.2023.05.003
基于卷积神经网络的无人机图像自动识别算法
Automatic Recognition Algorithm of UAV Image Based on Convolutional Neural Network
史宝岱 1徐艳召 1崔俊杰 1田裕 1张宗腾2
作者信息
- 1. 93057部队,辽宁四平 136400
- 2. 95835部队,新疆巴音郭楞蒙古自治州 841200
- 折叠
摘要
Abstract
The efficiency of deciphering the original image of the UAV is closely related to the speed of intelligence support.However,the current automatic recognition algorithms for synthetic aperture images and optical images are not mature enough,and there are problems such as large models and low recognition rates.Therefore,to improve the model recognition rate and make the model light-weight,a lightweight convolutional neural network algorithm that can effectively identify SAR images and optical remote sensing images is proposed.Firstly,the Residual Shrinkage Network is improved,a feature extraction module is constructed,the fully connected layer is replaced with a one-dimen-sional convolution with an adaptive K value,and spatial attention is added to the network to improve the threshold extraction efficiency.After that,the feature extraction module is used to build the mod-el,and the MSTAR data set,UC Merced Land-Use Data Set,SIRI-WHU two types of optical remote sensing images are used to detect the effect of the model.Experiment shows that the model is effective.关键词
卷积神经网络/SAR图像/光学遥感图像/残差收缩网络/空间注意力Key words
convolutional neural network/SAR images/optical remote sensing image/residual shrinkage network/spatial attention分类
信息技术与安全科学引用本文复制引用
史宝岱,徐艳召,崔俊杰,田裕,张宗腾..基于卷积神经网络的无人机图像自动识别算法[J].信息工程大学学报,2023,24(5):526-532,7.
