Researchers develop deep-learning method to predict daily activities Georgia Institute of Technology

Researchers from the School of Interactive Computing and the Institute for Robotics and Intelligent Machines developed a new method that teaches computers to “see” and understand what humans do in a typical day. The technique gathered more than 40,000 pictures taken every 30 to 60 seconds, over a 6 month period, by a wearable camera and predicted with 83 percent accuracy what activity that person was doing. Researchers taught the computer to categorize images across 19 activity classes. The test subject wearing the camera could review and annotate the photos at the end of each day (deleting any necessary for privacy) to ensure that they were correctly categorized. “It was surprising how the method’s ability to correctly classify images could be generalized to another person after just two more days…


Link to Full Article: Researchers develop deep-learning method to predict daily activities Georgia Institute of Technology