In the age of digital transformation, machine learning (ML) is rapidly becoming a pivotal technology in various sectors. One of ...

Discover how machine learning is helping researchers identify different groups of chronic obstructive pulmonary disease (COPD) patients in China and understand how their health conditions impact daily ...

Abstract: Unsupervised learning visible-infrared person re-identification (USL-VI-ReID) aims to learn modality-invariant features from unlabeled cross-modality data. However, existing approaches lack ...

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, ...

Summary: New research reveals that the brain may be learning even during unstructured, aimless exploration. By recording activity in tens of thousands of neurons, scientists found that the visual ...

There was an error while loading. Please reload this page. Hardware Trojan Detection using Unsupervised Learning and Simulation-Based Side-Channel Features Overview ...

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...