Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …

With the rapid development of deep learning technology and improvement in computing
capability, deep learning has been widely used in the field of hyperspectral image (HSI) …

Recently, a great many deep convolutional neural network (CNN)-based methods have
been proposed for hyperspectral image (HSI) classification. Although the proposed CNN …

In the last five years, deep learning has been introduced to tackle the hyperspectral image
(HSI) classification and demonstrated good performance. In particular, the convolutional …

Hyperspectral image (HSI) classification is one of the most important tasks in hyperspectral
data analysis. Convolutional neural networks (CNN) have been introduced to HSI …

Convolutional neural networks (CNNs) have been widely used for hyperspectral image
classification. As a common process, small cubes are first cropped from the hyperspectral …

Hyperspectral image (HSI) classification aims to assign each hyperspectral pixel with a
proper land-cover label. Recently, convolutional neural networks (CNNs) have shown …

In recent years, deep learning has been successfully applied to hyperspectral image
classification (HSI) problems, with several convolutional neural network (CNN) based …

Hyperspectral image classification (HSIC) methods based on convolutional neural network
(CNN) continue to progress in recent years. However, high complexity, information …