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Journal of Frontiers of Computer Science and Technology. 2022, (12) Core

Fast 3D-CNN Combined with Depth Separable Convolution for Hyperspectral Image ClassificationChinese Full TextEnglish Full Text (MT)

WANG Yan;LIANG Qi;School of Computer and Communication, Lanzhou University of Technology;

Abstract: 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 convolution model based on fast three-dimensional convolution neural networks（3D-CNN） and depth separable convolutions（DSC） is proposed.Firstly, incremental principal component analysis（IPCA） is used t... More
Keywords：

hyperspectral image（HSI） classification; spatial spectrum feature extraction; 3-dimensional convolutional neural networks（3D-CNN）; depthwise separable convolution（DSC）; deep learning;

  • Series：

    (I) Electronic Technology ＆ Information Science; (C) Architecture/ Energy/ Traffic/ Electromechanics, etc

  • Subject：

    Industrial Current Technology and Equipment; Automation Technology

  • Classification Code：

    TP751

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