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 …

Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in the
last four decades from being a sparse research tool into a commodity product available to a …

In hyperspectral image (HSI) classification, each pixel sample is assigned to a land-cover
category. In the recent past, convolutional neural network (CNN)-based HSI classification …

The joint use of multisource remote-sensing (RS) data for Earth observation missions has
drawn much attention. Although the fusion of several data sources can improve the accuracy …

Hyperspectral image (HSI) can provide rich spectral information which can be helpful for
accurate classification in many applications. Yet, incorporating spatial information in the …

Deep learning has achieved great successes in conventional computer vision tasks. In this
paper, we exploit deep learning techniques to address the hyperspectral image …

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 …

As one of the fundamental research topics in remote sensing image analysis, hyperspectral
image (HSI) classification has been extensively studied so far. However, how to …

Recent imaging science and technology discoveries have considered hyperspectral
imagery and remote sensing. The current intelligent technologies, such as support vector …

Edge-preserving features (EPFs) obtained by the application of edge-preserving filters to
hyperspectral images (HSIs) have been found very effective in characterizing significant …