Howells, G. and Fairhurst, M.C. and Bisset, D.L. (1996) Novel RAM-based neural networks for object recognition. In: Solomon, S.S. and Batchelor, B.G. and Waltz, F.M., eds. Proceedings of the society of photo-optical instrumentation engineers(SPIE). Spie - Int Soc Optical Engineering pp. 50-57. ISBN 0-8194-2310-6.
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This paper introduces a novel networking strategy for RAM-based Neurons which significantly improves the training and recognition performance of such networks whilst maintaining the generalisation capabilities achieved in previous network configurations. A number of different architectures are introduced each using the same underlying principles. Initially, features which are common to all architectures are described illustrating the basis of the underlying paradigm. Three architectures are then introduced illustrating different techniques for employing the paradigm to meet differing performance specifications. The architectures are described in terms of the structure of the neurons they employ. Greater detail of the various training and recognition algorithms employed by the architectures may be found in the referenced papers.
|Item Type:||Conference or workshop item (Paper)|
|Additional information:||Conference on Machine Vision Applications, Architectures, and Systems Integration V BOSTON, MA, NOV 18-19, 1996 Soc Photo Opt Instrumentat Engineers|
|Subjects:||Q Science > Q Science (General) > Q335 Artificial intelligence|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts|
|Depositing User:||R.F. Xu|
|Date Deposited:||04 Jun 2009 16:03|
|Last Modified:||04 Jun 2009 16:03|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/19248 (The current URI for this page, for reference purposes)|
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