Machine learning algorithm fully reconstructs LHC particle collisions

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Exploring electron microscopy and AI as key players for identifying pollen grains

Have you ever seen a hibiscus flower? Although its petals have a range of colors, what makes the trumpet-shaped flower more ...
IEEE

Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Frontiers

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

Although deep learning models dominate the field, conventional machine learning (ML) techniques have shown potential in brain tumor classification. The Gaussian Process Classifier (GPC), combined with ...
Visual Studio Magazine

Predicting the Future Using Azure Machine Learning

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
Frontiers

Classification of neurodegenerative diseases using brain effective connectivity and machine learning techniques: a systematic review

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 ...