Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

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 ...

Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

Introduction: Karst collapse monitoring is a complex task due to data sparsity, underground dynamics, and the demand for real-time risk assessment. Traditional approaches often fall short in ...

Abstract: This paper presents advanced feature extraction techniques for analyzing leakage current data from contaminated high voltage insulators, aimed at enhancing deep learning applications in ...

The EEG Classification Model project involves developing a machine learning model to classify brainwave patterns from EEG signals for applications like health monitoring and neurological disorder ...

ABSTRACT: The food recognition systems are available for foreign dishes but much work has not been done for our traditional dishes making it difficult to classify the traditional dishes and the ...

This Python package provides efficient linguistic feature extraction for text datasets (i.e. datasets with N text instances, in a tabular structure). If you want to use the spacy backbone, you will ...

Knowledge graphs (KGs) are the foundation of artificial intelligence applications but are incomplete and sparse, affecting their effectiveness. Well-established KGs such as DBpedia and Wikidata lack ...