Hyperspectral image (HSI) classification has become a hot topic in the field of remote
sensing. In general, the complex characteristics of hyperspectral data make the accurate …

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 …

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

A generative adversarial network (GAN) usually contains a generative network and a
discriminative network in competition with each other. The GAN has shown its capability in a …

Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications
because it benefits from the detailed spectral information contained in each pixel. Notably …

Hyperspectral image (HSI) classification is a critical task with numerous applications in the
field of remote sensing. Although convolutional neural networks have achieved remarkable …

Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …

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

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

Recently, deep learning has drawn broad attention in the hyperspectral image (HSI)
classification task. Many works have focused on elaborately designing various spectral …