Grants and Contributions:
Title:
Biologically inspired online novelty detection
Agreement Number:
964398
Agreement Value:
$199,870.00
Agreement Date:
Jan 11, 2021 - Sep 1, 2024
Description:
Artificial Intelligence (AI) based systems that have the ability to detect novelty is important because unexpected movement or the presence of unfamiliar objects are highly relevant for movement planning. In this case,
the use of drones for infrastructure inspection is explicitly dependent on a robust novelty detection system where it is much more important to detect that something is wrong than it is to successfully classify exactly what the
problem is. This Project seeks to explore and evaluate a variety of novelty detection algorithms, including both traditional machine learning algorithms and the more biologically-inspired algorithms. The Project will evaluate the
computational cost of running these algorithms online, the ability of these systems to learn on-line to adjust their expectations, and the robustness of their novelty detection on infrastructure-relevant tasks. Direct applications of
this system would be logistics infrastructure inspection, including railway lines, bridges, shipping containers and transmission-line inspections.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Waterloo, Ontario, CA N2L 3G1
Reference Number:
172-2020-2021-Q4-964398
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
119260685
Recipient Type:
Academia
Additional Information:
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 365 days.
Amendment Date
Feb 22, 2022
Recipient's Legal Name:
University of Waterloo
Federal Riding Name:
Waterloo
Federal Riding Number:
35112
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710
Amendments: