The future of surveying, mapping and global sustainability requires pairing the best of satellite technology with human ...

On May 17, Forbes China officially released the results of the "2026 Forbes China AI TECH Enterprises TOP 50" selection, jointly initiated and evaluated ...

Class-constrained classification problems arise in scenarios where predictions must satisfy resource limitations. For example, classifying loan applicants to decide who receives funding within a ...

The American Association of Clinical Endocrinology (AACE) has released the 2026 update to its consensus statement algorithm for the management of adults with type 2 diabetes (T2D). The statement was ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

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 ...

Abstract: The issue of limited labeled samples is still grave in hyperspectral image classification. Semisupervised learning (SSL) utilizing both labeled and unlabeled samples promotes a solution to ...

Modern methods of infrared (IR) spectroscopy yield full IR absorbance spectra in arrays, forming hyperspectral images. End-to-end processing of these images via deep learning seems ideal for ...

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 ...