Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research
field and is considered a non-invasive tool for tissue diagnosis. This review article gives a …

Graph neural networks (GNNs), as an effective learning framework for graph structure data
representation, have been applied to hyperspectral images (HSIs) classification tasks …

New developments in instrumentation and data analysis have further improved the
perspectives of hyperspectral imaging in clinical use. Thus, hyperspectral imaging can be …

Hyperspectral imaging technology has been popularly applied in remote sensing because it
collects echoed signals from across the electromagnetic (EM) spectrum and thereby …

Convolutional Neural Networks (CNN) have become the core of modern machine learning
approaches. In addition to its inspiring interior design idea, the success of CNN depends …

Nowadays, the deep learning concept is used to solve Computer Vision's many problems,
as remote-sensing image classification. Hyperspectral image (HSI) classification is a major …

Due to the growth of society and the steady progress of economic construction, people are
no longer only satisfied with the material needs of life, but more begin to pursue spiritual …

The study of classification algorithms based on support vector machines is a popular
research field. This article improves the deep multiple kernel learning model based on …