Machine learning accelerates analysis of fusion materials

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

machine learning

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eLife

New idtracker.ai rethinks multi-animal tracking as a representation learning problem to increase accuracy and reduce tracking time

Identification of each animal in a collective becomes possible even when individuals are never all visible simultaneously, enabling faster and more accurate analysis of collective behavior.

In bone imaging, machine learning accelerates research progress and uncovers hidden patterns

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...
Tech Xplore

Compression technique makes AI models leaner and faster while they're still learning

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
Open Heart

Periprocedural evaluation of patients with BAV stenosis undergoing TAVR: a machine learning-based study

Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
IEEE

Image Recognition & Classification with Machine Learning

Abstract: Image recognition and classification, powered by machine learning, is a rapidly advancing field with broad applications across various industries. Machine learning techniques, especially ...
Frontiers

Traditional machine learning in biomedical image analysis: before you go too deep

Traditional machine learning (TML) algorithms remain indispensable tools for the analysis of biomedical images, offering significant advantages in multimodal data integration, interpretability, ...
Rome Sentinel

SRC gets AFRL contract for next-gen AI, machine learning

ROME — SRC, a not-for-profit defense research and development company headquartered in Syracuse with an office in Rome on the Griffiss Business and Technology Park, has been awarded a $24M contract by ...
IEEE

Federated Learning for Medical Image Classification: A Comprehensive Benchmark

Abstract: The federated learning (FL) paradigm is well-suited for the field of medical image analysis, as it can effectively cope with machine learning on isolated multi-center data while protecting ...