IEEE

A Somatotype Classification Approach Based on Generative AI and Frontal Images of Individuals

Abstract: Somatotype is a definition that classifies human bodies according to their shape, and its determination is crucial for evaluating and improving athletic performance. However, the traditional ...

Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
pv magazine International

PV inverter output and anomalies predicted without environmental sensors

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
IEEE

Enhancing Defect Classification in Solar Panels With Electroluminescence Imaging and Advanced Machine Learning Strategies

Abstract: Electroluminescence (EL) imaging is the most widely used diagnostic technique for identifying flaws at every stage of the production, installation, and operation of solar modules. This ...