Welcome to the University of Waterloo Centre for Pattern Analysis and Machine Intelligence (CPAMI).
The center collaborates with a number of industrial partners at the local and the provincial levels and also cooperates with other centres at the University of Waterloo and at other universities.
The centre is interdisciplinary, bringing together experts from artificial intelligence, computer science, software engineering, cognitive science, electrical and computer engineering, mechanical and mechatronics engineering, systems design engineering, civil engineering, management sciences, chemical engineering, mathematics, and statistics.
News
15th International Conference on Image Analysis and Recognition (ICIAR) 2018
The International Conference on Image Analysis and Recognition aims to bring together researchers in the fields of Image Processing, Image Analysis and Pattern Recognition. The conference will address recent advances in theory, methodologies and applications. The scientific program will include invited speakers and fully refereed contributions that will be published in the conference proceedings.
CPAMI Distinguished Professor Andrew Wong Receives Best Paper Award at DMIN’17
Professor Andrew K.C. Wong, Dr. Peiyuan Zhou and Mr. Antonio Sze-To are the recipients of the Best Paper Award at the 13th International Conference on Data Mining 2017 (DMIN'17) held in Las Vegas, USA.
CPAMI Researchers Develop AI Tools for Detecting People Texting while Driving
Computer algorithms developed by engineering researchers at the University of Waterloo can accurately determine when drivers are texting or engaged in other distracting activities.
The system uses cameras and artificial intelligence (AI) to detect hand movements that deviate from normal driving behavior and grades or classifies them in terms of possible safety threats.
Fakhri Karray, an electrical and computer engineering professor at Waterloo, said that information could be used to improve road safety by warning or alerting drivers when they are dangerously distracted.