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Optimal classifier combination rules for verification and identification systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Matching systems can be used in different operation tasks such as verification task and identification task. Different optimization criteria exist for these tasks - reducing cost of acceptance decisions for verification systems and minimizing misclassification rate for identification systems. In this paper we show that the optimal combination rules satisfying these criteria are also different. The difference is caused by the dependence of matching scores produced by a single matcher and assigned to different classes. We illustrate the theory by experiments with biometric matchers and handwritten word recognizers.

Original languageEnglish
Title of host publicationMultiple Classifier Systems - 7th International Workshop, MCS 2007, Proceedings
PublisherSpringer Verlag
Pages387-396
Number of pages10
ISBN (Print)9783540724810
DOIs
StatePublished - 2007
Event7th International Workshop on Multiple Classifier Systems, MCS 2007 - Prague, Czech Republic
Duration: May 23 2007May 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4472 LNCS

Conference

Conference7th International Workshop on Multiple Classifier Systems, MCS 2007
Country/TerritoryCzech Republic
CityPrague
Period05/23/0705/25/07

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