Contemporary research suggests that AI improves efficiency in areas such as fraud detection and portfolio optimisation due to its vast data and analytical prowess. However, it also bears the risks of ...

Data clustering and classification have become indispensable for extracting actionable insights from large-scale, heterogeneous datasets characterised by high volume, velocity and variety. Clustering ...

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...

In machine learning, it is often necessary to statistically compare the overall performance of two algorithms (e.g., our proposed algorithm and each compared baseline) based on multiple benchmark ...

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

The proposed method integrates Discrete Wavelet Transformation (DWT) and Independent Component Analysis (ICA) for noise removal, followed by a robust Kalman filter enhanced with convex optimization to ...

For all 4 algorithms, more balanced classes (multiplier: 0.93-0.96 for a 1% increase in minority class proportion) were associated with decreased sample size. Other characteristics varied in ...

Abstract: Heart disease, which includes various circulatory illnesses that largely impact the structure and function of the heart, is a prevalent primary cause of morbidity and mortality. This ...

Abstract: 3D point cloud classification is one of the important tasks before autonomous driving technology. However, the traditional PointNet++ algorithm has some limitations, such as sensitivity to ...