ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

The first official sighting of AMD's Radeon AI Pro R9700 out in the wild is now in the books after a user on Reddit scored a Gigabyte variant and then promptly posted a picture of the retail packaging ...

DUBAI, United Arab Emirates--(BUSINESS WIRE)--Dubai has launched the world’s first icon-based classification system to represent the level of human–machine collaboration in the process of producing ...

This project represents a collaborative research initiative between the Machine Intelligence Lab and Department of Ophthalmology, Sichuan University focusing on advanced deep learning solutions for ...

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...

Department of Preventive Medicine, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China Background: Effective connectivity (EC) refers to the ...

This repo contains state-of-the-art deep learning models for industrial anomaly detection, defect segmentation, detection, and classification, with other industrial machine vision applications.

Abstract: Accurate and efficient brain tumor diagnosis remains a critical challenge in medical imaging. This study proposes a novel framework that integrates fuzzy logic-based segmentation with deep ...

Abstract: Skin diseases (SDs), particularly skin cancer, are leading causes of morbidity and mortality worldwide, with early detection being crucial for improving patient outcomes. Dermoscopy, a ...

Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR ...