Profs use AI to track hockey games better
The growing field of hockey analytics currently relies on the manual analysis of video footage from games. But the speed of hockey makes manually tracking and analyzing each player during a game very difficult and prone to human error.
Dr. David Clausi and Dr. John Zelek, both professors in the Department of Systems Design Engineering, with research assistant professor Yuhao Chen and a team of graduate students, have developed an AI tool that uses deep learning techniques to automate and improve player tracking analysis.