A team of scientists at Georgia Southern University has combined both spatial and temporal attention mechanisms to develop a new approach for PV inverter fault detection. Training the new method on a ...

In 2012, Dr. Patil designed a distinct software toolbox for deep learning in Matlab because, at the time of her master’s degree research, there was no general tool available to experiment with ...

“Geometric deep learning is likely going to be part of the standard AI-powered engineering process in five years for most companies,” says Altair’s VP of engineering data science ...

Presentation 1: Deep Learning in Deep Sequencing: Detecting and Monitoring Low-Abundance ctDNA By Bingsi Li, Ph.D. Bingsi Li will showcase how ultra-deep sequencing, combined with deep learning, ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Technical Aspects of Deep Learning in Medicine: Explore the technical foundations of deep learning, including neural network architectures and their applications in medical research and practice. AI ...

The integration of deep learning in neuroimaging enhances diagnostic capabilities, offering new insights into neurological disorders and treatment responses.

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly a… ...

A deep-learning algorithm helped identify new compounds that are effective against antibiotic-resistant infections in mice, opening the door to AI-guided drug discovery ...

Researchers used deep learning to resurrect antibiotic peptides from extinct organisms, offering new solutions for combating antibiotic resistance.