Real-time object tracking using deep learning
SOURCE Citation
Isah, Haruna; Mohammed,, Lubna; Akanbi, Adegoke; Kaushik, Priyanshu; and Kim, Dohee, "Real-time object tracking using deep learning" (2024). Generator at Sheridan. 18.
https://source.sheridancollege.ca/conferences_creates/2024/2024/18
Location
Hazel McCallion Campus
Start Date
23-10-2024 12:00 PM
End Date
23-10-2024 1:30 PM
Description
Centre for Applied AI
Faculty of Applied Science and Technology
The explosive growth in the number of vehicles in use today presents several societal and environmental challenges, especially in urban centres. Learn more about how the Centre for Applied AI collaborated with LocoMobi on a project that developed an algorithm to enhance the performance of a system that addresses the challenge of character misrecognition and errors in licence plate scanning.
Copyright
© Sheridan College
Real-time object tracking using deep learning
Hazel McCallion Campus
Centre for Applied AI
Faculty of Applied Science and Technology
The explosive growth in the number of vehicles in use today presents several societal and environmental challenges, especially in urban centres. Learn more about how the Centre for Applied AI collaborated with LocoMobi on a project that developed an algorithm to enhance the performance of a system that addresses the challenge of character misrecognition and errors in licence plate scanning.
Comments
Interactive Booth