Classification of Hyperspectral Remote Sensing Images Based on Three-Dimensional Convolutional Neural Network Model

Author:

Zhao Pan,Yin Xiaoling,Chen Shida

Publisher

Springer Nature Switzerland

Reference19 articles.

1. Sadovnychiy, S.: Gabor features extraction and land-cover classification of urban hyperspectral images for remote sensing applications. Remote Sensing 13(15), 2914 (2021)

2. Jijon-Palma, M.E., Kern, J., Amisse, C., et al.: Improving stacked-autoencoders with 1D convolutional-nets for hyperspectral image land-cover classification. J. Appl. Remote. Sens. 2, 15 (2021)

3. Cao, H., Han, X., Li, J., et al.: Hyperspectral remote sensing image classification based on EMP and SVM with composite kernel. Geospatial Inf. 19(11), 14–18 (2021)

4. Liu, J., Ban, W., Chen, Y., et al.: Multi-dimensional CNN fused algorithm for hyperspectral remote sensing image classification. Chinese Journal of Lasers 48(16), 153–163 (2021)

5. Peng, Y., Wang, X., Zhang, J., et al.: Pre‐training of gated convolution neural network for remote sensing image super‐resolution. IET Image Processing 15(5), 11791188 (2021)

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