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Proceedings Paper

Concurrent grammar inference machines for 2-D pattern recognition: a comparison with the level set approach
Author(s): K. P. Lam; P. Fletcher
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Paper Abstract

Parallel processing promises scalable and effective computing power which can handle the complex data structures of knowledge representation languages efficiently. Past and present sequential architectures, despite the rapid advances in computing technology, have yet to provide such processing power and to offer a holistic solution to the problem. This paper presents a fresh attempt in formulating alternative techniques for grammar learning, based upon the parallel and distributed model of connectionism, to facilitate the more cognitively demanding task of pattern understanding. The proposed method has been compared with the contemporary approach of shape modelling based on level sets, and demonstrated its potential as a prototype for constructing robust networks on high performance parallel platforms.

Paper Details

Date Published: 11 February 2009
PDF: 12 pages
Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 724515 (11 February 2009); doi: 10.1117/12.806035
Show Author Affiliations
K. P. Lam, Univ. of Keele (United Kingdom)
P. Fletcher, Univ. of Keele (United Kingdom)


Published in SPIE Proceedings Vol. 7245:
Image Processing: Algorithms and Systems VII
Nasser M. Nasrabadi; Syed A. Rizvi; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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