Fast 3D-CNN Combined with Depth Separable Convolution for Hyperspectral Image Classification

Fast 3D-CNN Combined with Depth Separable Convolution for Hyperspectral Image Classification

In the process of feature extraction and classification of hyperspectral images using convolution neural networks, there are problems such as insufficient extraction of spatial spectrum features and too many layers of networks, which lead to large parameters and complex calculations. A lightweight c...

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Bibliographic Details
Main Author: WANG Yan, LIANG Qi
Format: Article
Language:zho
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 2022-12-01
Series:Jisuanji kexue yu tansuo
Subjects:
|hyperspectral image (hsi) classification|spatial spectrum feature extraction|3-dimensional convolutional neural networks (3d-cnn)|depthwise separable convolution (dsc)|deep learning
Online Access:http://fcst.ceaj.org/fileup/1673-9418/PDF/2103051.pdf

Internet

http://fcst.ceaj.org/fileup/1673-9418/PDF/2103051.pdf

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