Hyperspectral imaging is applied in the medical field for automated diagnosis of diseases,
especially cancer. Among the various classification algorithms, the most suitable ones are …

Hyperspectral image (HSI) contains abundant spectral-spatial information, which is widely
used in many fields. HSI classification is a fundamental and important task, which aims to …

In the last decades, technological advances have led to a considerable increase in
computing power constraints to simulate complex phenomena in various application fields …

Cardiovascular Diseases (CVDs) stand as the leading cause of mortality worldwide.
Detecting subtle heart sounds alterations in the early stages of CVDs can be crucial for an …

Hyperspectral imaging (HSI) captures detailed spectral information across numerous
wavelengths, providing superior object characterization to conventional RGB imaging …

Principal component analysis (PCA) is essential for diminishing the number of dimensions
across various fields, preserving data integrity while simplifying complexity. Eigenfaces, a …

This paper delves into intelligent image feature extraction, centering on robust subspace
learning methods. It investigates their application to handle noisy and diverse image data …

In this paper, a novel approach for cluster analysis of online learning behaviors among
Chinese language learners is proposed. Given the susceptibility of Fuzzy C-Means (FCM) …

The end member hybrid profile (EMHP) representing end individuals extracted from
multispectral photos (MSI) and spectral libraries has been delivered for unsupervised land …

A* algorithm is one of the artificial intelligences searching algorithms that is used to find the
shortest rout of path traversal. Executing the algorithm in one processor is not efficient …