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Collaborative Supervised Learning Issues for Machine Vision: Parallelising People Power


Sheridan, P and Drew, S and Venema, S and Sun, C, Collaborative Supervised Learning Issues for Machine Vision: Parallelising People Power, Proceedings of the International Conference on Imaging Science, Systems and Technology, CISST '03, June 23-26, 2003, Las Vegas, USA, pp. 640-644. ISBN 1892512475 (2003) [Refereed Conference Paper]


This paper describes a computer vision system in the context of exploiting parallelism. The key contribution is a description of a network design that breaks a long-standing bottleneck in the supervision phase of the vision process. The proposed solution draws from and contributes to the disciplines of machine learning, computer vision and collaborative editing. The significance of the solution is that it provides the means by which complex visual tasks such as mammography can be learned by an artificial vision system.

Item Details

Item Type:Refereed Conference Paper
Research Division:Language, Communication and Culture
Research Group:Communication and media studies
Research Field:Communication technology and digital media studies
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Drew, S (Dr Steve Drew)
ID Code:112165
Year Published:2003
Deposited By:Curriculum and Academic Development
Deposited On:2016-10-28
Last Modified:2016-10-28

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