Deep learning techniques have boosted the performance of hyperspectral image (HSI)
classification. In particular, convolutional neural networks (CNNs) have shown superior …

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

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

Convolutional neural networks (CNNs) have recently shown outstanding capability for
hyperspectral image (HSI) classification. In this work, a novel CNN model is proposed, which …

Convolutional neural network (CNN) has demonstrated to be a powerful tool for
hyperspectral images (HSIs) classification. Previous CNN-based HSI classification methods …

The profound impact of deep learning and particularly of convolutional neural networks
(CNNs) in automatic image processing has been decisive for the progress and evolution of …

As a powerful visual model, convolutional neural networks (CNNs) have demonstrated
remarkable performance in various visual recognition problems, and attracted considerable …

Capsule networks can be considered to be the next era of deep learning and have recently
shown their advantages in supervised classification. Instead of using scalar values to …

Recently, the hyperspectral image (HSI) classification methods based on convolutional
neural networks (CNN) have developed rapidly with the advance of deep learning (DL) …

In recent years, convolutional neural networks (CNNs) have been introduced for pixel-wise
hyperspectral image (HSI) classification tasks. However, some problems of the CNNs are …