On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

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 …

Deep learning (DL) based methods represented by convolutional neural networks (CNNs)
are widely used in hyperspectral image classification (HSIC). Some of these methods have …

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) …

Recurrent neural networks and Transformers have recently dominated most applications in
hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies …

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 …

Pan-sharpening aims to generate high-resolution multi-spectral (MS) images by fusing PAN
images and low-resolution MS images. Despite its great advances, most existing pan …

In recent years, researchers have paid increasing attention on hyperspectral image (HSI)
classification using deep learning methods. To improve the accuracy and reduce the training …

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 …

Deep neural network has been extensively applied to hyperspectral image (HSI)
classification recently. However, its success is greatly attributed to numerous labeled …