Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

Outstanding steps towards intelligent transportation systems with autonomous vehicles have
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …

Vision transformers (ViTs) have been trending in image classification tasks due to their
promising performance when compared with convolutional neural networks (CNNs). As a …

In recent years, convolutional neural networks (CNNs) have drawn significant attention for
the classification of hyperspectral images (HSIs). Due to their self-attention mechanism, the …

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 …

Hyperspectral images (HSIs) provide detailed spectral information through hundreds of
(narrow) spectral channels (also known as dimensionality or bands), which can be used to …

Model-driven methods and data-driven methods have been widely developed for
hyperspectral image (HSI) denoising. However, there are pros and cons in both model …

Hyperspectral imaging (HSI) is a powerful tool that can capture and analyze a range of
spectral bands, providing unparalleled levels of precision and accuracy in data analysis …

Mixed noise pollution in HSI severely disturbs subsequent interpretations and applications.
In this technical review, we first give the noise analysis in different noisy HSIs and conclude …

Remote sensing provides valuable information about objects and areas from a distance in
either active (eg, radar and lidar) or passive (eg, multispectral and hyperspectral) modes …