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Development of a Corrosion and Damage Detection Application on 3D Reconstructed Subsea Objects
qualiTEAS’ product, Argus 1.21, is machine learning based computer vision application that can analyze images of offshore structures and detect corrosion-mediated damages. Through this project, qualiTEAS is aimed to develop a next-generation machine vision solution that can detect corrosion impact on a 3D representation of the asset.
Faculty Supervisor:
Stephen Czarnuch
Student:
Partner:
qualiTEAS Inc
Discipline:
Computer science
Sector:
Professional, scientific and technical services
University:
Memorial University of Newfoundland
Program:
Business Strategy Internship
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