Multistrategy machine-learning vision system

Barry A. Roberts

doi:10.1117/12.142799

13 April 1993 Multistrategy machine-learning vision system

Barry A. Roberts

Proceedings Volume 1838, 21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications; (1993) https://doi.org/10.1117/12.142799
Event: Applied Imaging Pattern Recognition, 1992, Washington, DC, United States

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.

Citation Download Citation

Barry A. Roberts "Multistrategy machine-learning vision system", Proc. SPIE 1838, 21st AIPR Workshop on Interdisciplinary Computer Vision: An Exploration of Diverse Applications, (13 April 1993); https://doi.org/10.1117/12.142799

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