For many parents, conversations about screen time come with guilt. We count minutes, set timers, and wonder if we’re doing enough, or too much, to protect ...
Discover how machine learning, a vital aspect of artificial intelligence, learns from data to enhance decision-making and ...
The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...
The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...
Machine learning is revolutionizing fundamental science by tackling long-standing mathematical challenges. A key example is ...
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Introduction: Myocardial ischemia can result in severe cardiovascular complications. However, the impact of clinical factors on myocardial ischemia in individuals with T2DM remains unclear. we applied ...
Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...
ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...
Abstract: Magnetic resonance imaging (MRI) is powerful in medical diagnostics, yet high-field MRI, despite offering superior image quality, incurs significant costs for procurement, installation, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback