Compact Global-Local Convolutional Network With Multifeature Fusion and Learning for Scene Classification in Synthetic Aperture Radar Imagery
Compact Global-Local Convolutional Network With Multifeature Fusion and Learning for Scene Classification in Synthetic Aperture Radar Imagery
复制标题
具有多特征融合和学习的紧凑全局局部卷积网络用于合成孔径雷达图像中的场景分类
DOI：
10.1109/jstars.2021.3096941
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发表时间：
2021
影响因子：
5.5
通讯作者：
Peng Wang
中科院分区：
文献类型：
--
作者：
Kang Ni;Pengfei Liu;Peng Wang
卷积神经网络（CNN）的特征学习引起了人们的关注，并在合成孔径雷达（SAR）图像场景分类方面取得了良好的表现。但是，现有的卷积功能学习的表现
Feature learning of convolutional neural networks (CNNs) has gained considerable attention and achieved good performance on synthetic aperture radar (SAR) image scene classification. However, the performance of the existing convolutional feature learning