Related projects
Discover more projects across a range of sectors and discipline — from AI to cleantech to social innovation.
Graph Kolmogorov-Arnold Networks for 3D point cloud data analysis, with applications in tree species recognition and brain connectivity analysis
This project aims to develop advanced deep learning models that combine graph-based neural networks with Kolmogorov-Arnold Networks (KAN) to improve the analysis of 3D point cloud data. These models will be applied to real-world problems such as identifying tree species from laser scanning data and studying brain connectivity from medical imaging. The collaboration will benefit Concordia University by advancing research in AI and 3D data processing, strengthening its expertise in environmental and medical applications. ENSIAS, Mohammed V University, will gain hands-on experience with novel neural network architectures and practical deployment strategies, enhancing its capacity for innovation in machine learning and data science. Together, the institutions will foster knowledge exchange and create solutions with strong academic and societal impact.
Faculty Supervisor:
Abdessamad Ben Hamza
Student:
Partner:
Université Mohammed V de Rabat
Discipline:
Computer science
Sector:
Artificial Intelligence
University:
Concordia University
Program:
Globalink Research Award
Current openings
Find the perfect opportunity to put your academic skills and knowledge into practice!
Find Projects
International
Load More
International
Load More
Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.