Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

Over the past three decades, significant developments have been made in hyperspectral
imaging due to which it has emerged as an effective tool in numerous civil, environmental …

Recently, the graph convolutional network (GCN) has drawn increasing attention in the
hyperspectral image (HSI) classification. Compared with the convolutional neural network …

Hyperspectral (HS) imaging provides rich spatial and spectral information and extends
image inspection beyond human perception. Existing approaches, however, suffer from …

Hyperspectral image (HSI) classification is one of the most important tasks in hyperspectral
data analysis. Convolutional neural networks (CNN) have been introduced to HSI …

Transformer architectures have become state-of-the-art models in computer vision and
natural language processing. To a significant degree, their success can be attributed to self …

This study provides an overview of the techniques, shortcomings, and strengths of remote
sensing (RS) applications in the effective retrieval and monitoring of water quality …

Remote sensing approaches to measuring inland water quality date back nearly 50 years to
the beginning of the satellite era. Over this time span, hundreds of peer-reviewed …

The development and uptake of field deployable hyperspectral imaging systems within
environmental monitoring represents an exciting and innovative development that could …

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications,
especially in disease diagnosis and image-guided surgery. HSI acquires a three …