Due to the advantages of deep learning, in this paper, a regularized deep feature extraction
(FE) method is presented for hyperspectral image (HSI) classification using a convolutional …

Hyperspectral image (HSI) classification is a core task in the remote sensing community,
and recently, deep learning-based methods have shown their capability of accurate …

In recent years, airborne and spaceborne hyperspectral imaging systems have advanced in
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …

Based on high-temperature and low-oxygen diffusion clean combustion technology, a novel-type
of heat flue in a coke oven was designed in this paper. By changing the internal …

Classification is one of the most popular topics in hyperspectral remote sensing. In the last
two decades, a huge number of methods were proposed to deal with the hyperspectral data …

Hyperspectral data classification is a hot topic in remote sensing community. In recent years,
significant effort has been focused on this issue. However, most of the methods extract the …

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 …

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 variety …

Hyperspectral image classification has been a vibrant area of research in recent years. Given
a set of observations, ie, pixel vectors in a hyperspectral image, classification approaches …

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