Approach to performance optimisation in frequency-weighted memory network pattern classifiers

Fairhurst, Michael; Wahab, H. M. S. Abdel

doi:10.1049/el:19870779

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Cited by 7 publications

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“…Four distinct classifiers are chosen. FWS is the frequency weighted n-tuple classifier [3]. The sn-tuple [7] is a variant of the the FWS where a collection of n-tuples scan the chain code representations of the pattern images.…”

Section: A Comparisonmentioning

confidence: 99%

An improved learning scheme for the moving window classifier

Hoque

Fairhurst²

Proceedings of Sixth International Conference on Document Analysis and Recognition

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The Moving Window Classijier (MWC) is a simple and eficient classifier structure which, although shown to be capable of promising performance in a variety of tasks such as face recognition, its common application is a tool in text recognition. Various measures have been proposed to improve the MWC classification speed and to reduce memory space requirement. This paper introduces techniques for improving the MWC classification accuracy without losing any of gains previously achieved. These performance enhancement schemes ure readily applicable to a range of related classijiers and hence provide a generalized method for enhancement in a variety of tasks.

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Section: A Comparisonmentioning

confidence: 99%