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A Theory of Multiple Classifier Systems And Its Application to Visual Word Recognition (1992)
| Citations: | 34 - 8 self |
BibTeX
@MISC{Ho92atheory,
author = {Tin Kam Ho},
title = {A Theory of Multiple Classifier Systems And Its Application to Visual Word Recognition},
year = {1992}
}
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Abstract
Despite the success of many pattern recognition systems in constrained domains, problems that involve noisy input and many classes remain difficult. A promising direction is to use several classifiers simultaneously, such that they can complement each other in correctness. This thesis is concerned with decision combination in a multiple classifier system that is critical to its success. A multiple classifier system consists of a set of classifiers and a decision combination function. It is a preferred solution to a complex recognition problem because it allows simultaneous use of feature descriptors of many types, corresponding measures of similarity, and many classification procedures. It also allows dynamic selection, so that classifiers adapted to inputs of a particular type may be applied only when those inputs are encountered. Decisions by the classifiers are represented as rankings of the class set that are derivable from the results of feature matching. Rank scores contain more ...
Keyphrases
multiple classifier system visual word recognition particular type several classifier promising direction many classification procedure noisy input simultaneous use many pattern recognition system many class constrained domain class set decision combination many type feature descriptor decision combination function complex recognition problem preferred solution dynamic selection feature matching
