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Proceedings Paper

Multistrategy machine-learning vision system
Author(s): Barry A. Roberts
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Paper Abstract

Advances in the field of machine learning technology have yielded learning techniques with solid theoretical foundations that are applicable to the problems being encountered by object recognition systems. At Honeywell an object recognition system that works with high-level, symbolic, object features is under development. This system, named object recognition accomplished through combined learning expertise (ORACLE), employs both an inductive learning technique (i.e., conceptual clustering, CC) and a deductive technique (i.e., explanation-based learning, EBL) that are combined in a synergistic manner. This paper provides an overview of the ORACLE system, describes the machine learning mechanisms (EBL and CC) that it employs, and provides example results of system operation. The paper emphasizes the beneficial effect of integrating machine learning into object recognition systems.

Paper Details

Date Published: 13 April 1993
PDF: 12 pages
Proc. SPIE 1838, 21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications, (13 April 1993); doi: 10.1117/12.142799
Show Author Affiliations
Barry A. Roberts, Honeywell Inc. (United States)


Published in SPIE Proceedings Vol. 1838:
21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications
Jane Harmon, Editor(s)

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