Human activity recognition is a challenging problem with many applications including visual surveillance, human-computer interactions, autonomous driving and entertainment. In this study, we propose a ...

MINNEAPOLIS — A deep learning model trained on fundus photographs showed promise in the detection of severe glaucoma, with lower accuracy in mild to moderate cases, according to a poster ...

Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Researchers created an attention-multiple-instance deep learning AI model to predict whether indeterminate thyroid nodules were benign or malignant.

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome The methods help identify 'footprints' that indicate binding sites and reveal ...

A novel universal deep learning model for segmentation of automated optical inspection images for both PCBA and semiconductor components.

It utilizes advanced adaptive algorithms, aiming to redefine mathematics instruction and impact students, teachers, and parents.