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 …

The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to
the leading cause of cancer related mortality. The treatment procedure of the brain tumor …

Recent advancements in deep learning techniques have spurred considerable interest in
their application to hyperspectral imagery processing. This paper provides a comprehensive …

Sporadic ocean color events with characteristic spectra, in particular algal blooms, call for
quick delivery of high-resolution remote sensing data for further analysis. Motivated by this …

Hyperspectral imaging (HSI) is a competitive remote sensing technique in several fields,
from Earth observation to health, robotic vision, and quality control. Each HSI scene contains …

The modelling of drought is of utmost importance for the efficient management of water
resources. This article used the adaptive neuro-fuzzy interface system (ANFIS), multilayer …

Deep neural networks (DNNs) have emerged as a relevant tool for the classification of
remotely sensed hyperspectral images (HSIs), with convolutional neural networks (CNNs) …

With the wide applications of the unmanned aerial vehicle (UAV) in the civilian and military
fields, its operational safety has drawn much attention. A series of fault detection methods …

Dimensionality reduction represents a critical preprocessing step in order to increase the
efficiency and the performance of many hyperspectral imaging algorithms. However …

Soluble solids content (SSC) is one of the important components for evaluating fruit quality.
The rapid development of hyperspectral imagery provides an efficient method for non …