Deep learning models have shown excellent performance in the hyperspectral remote
sensing image (HSI) classification. In particular, convolutional neural networks (CNNs) have …

Deep learning methods have shown their marvel performance on hyperspectral image (HSI)
classification tasks. In particular, algorithms based on convolution neural network (CNN) …

Models based on capsule neural network (CapsNet), a novel deep learning method, have
recently made great achievements in hyperspectral remote sensing image (HSI) …

Hyperspectral remote sensing images (HSIs) are rich in spectral-spatial information. The
deep learning models can help to automatically extract and discover this rich information …

In this letter, an alternative data-driven HSI classification model based on CapsNet is
proposed rather than recently predominant convolutional neural network (CNN)-based …

In recent years, deep learning algorithms, particularly convolutional neural networks
(CNNs), have significantly improved the performance of the hyperspectral image (HSI) …

Limited training data, high dimensionality, image complexity, and similarity between classes
are challenges confronting hyperspectral image (HSI) classification often resulting in …

Recently, convolutional neural networks (CNNs) have attracted enormous attention in
pattern recognition and demonstrated excellent performance in hyperspectral image (HSI) …

Theconvolution neural network (CNN) has recently shown the good performance in
hyperspectral image (HSI) classification tasks. Many CNN-based methods crop image …

Convolutional neural networks (CNNs) have recently exhibited an excellent performance in
hyperspectral image classification tasks. However, the straightforward CNN-based network …