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Research News

Texas A&M University researchers have developed a new algorithm based on deep learning that can take low-resolution images and generate their high-resolution counterparts in real time.

Travel time studies in urban areas have shown that delays caused by intersections make up 12-55% of daily commute travel. A research team led by Dr. Guni Sharon has developed a self-learning system that utilizes machine learning to improve the flow of traffic at intersections.

A team of researchers at the Precise Advanced Technologies and Health Systems for Underserved Populations center are developing a new way to approach diet monitoring to benefit the more than 30 million Americans living with Type 2 diabetes.