The growth of Hyperspectral Image (HSI) analysis is due to technology advancements that
enable cameras to collect hundreds of continuous spectral information of each pixel in an …

Controlling and managing surface source pollution depends on the rapid monitoring of total
nitrogen in water. However, the complex factors affecting water quality (plant shading and …

Wavelet transform is being widely used in the field of information processing. One-
dimension and two-dimension quantum wavelet transforms have been investigated as …

An airborne hyperspectral imaging system is typically equipped on an aircraft or unmanned
aerial vehicle (UAV) to capture ground scenes from an overlooking perspective. Due to the …

This study addresses image denoising alongside the compression and reconstruction of
hyperspectral images (HSIs) using deep learning techniques, since the research community …

Epilepsy becomes one of the most frequently arising brain disorder, and it is marked by the
unexpected occurrence of frequent seizures. In this study, the University of the Boon …

Deep-learning-based methods have seen a massive rise in popularity for hyperspectral
image classification over the past few years. However, the success of deep learning is …

In this research, we study a new metaheuristic algorithm called Moth–Flame Optimization
(MFO) for hyperspectral band selection. With the hundreds of highly correlated narrow …

As an extremely efficient preprocessing tool, superpixels have become more and more
popular in various computer vision tasks. Nevertheless, there are still several drawbacks in …

Convolutional neural networks (CNNs) have gained popularity for categorizing
hyperspectral (HS) images due to their ability to capture representations of spatial-spectral …