Neural network-based fuzzy observer with application to facial analysis

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dc.contributor.authorPark, GTko
dc.contributor.authorBien, Zeung namko
dc.date.accessioned2013-03-03T08:43:24Z-
dc.date.available2013-03-03T08:43:24Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2000-02-
dc.identifier.citationPATTERN RECOGNITION LETTERS, v.21, no.2, pp.93 - 105-
dc.identifier.issn0167-8655-
dc.identifier.urihttp://hdl.handle.net/10203/78021-
dc.description.abstractHuman facial wrinkles can be effectively utilized for facial analysis. It is not an easy task, however, to extract features of wrinkledness directly from a camera image of a human face. For one thing, it is difficult to construct appropriate mathematical models for wrinkle features. In this work, a fuzzy observer is proposed as a means of providing linguistic descriptions about the image of a human face with wrinkles. In the proposed observer, some well-defined classical image features and numerical information are transformed into fuzzy numbers. A feedforward multilayered artificial neural network (ANN) is employed for parameter adjustment of the fuzzy observer based on the available crisp-input fuzzy-output sample sets. An experiment is performed to demonstrate that the facial wrinkles can be indirectly estimated by the proposed fuzzy observer. (C) 2000 Elsevier Science B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.titleNeural network-based fuzzy observer with application to facial analysis-
dc.typeArticle-
dc.identifier.wosid000085423600001-
dc.identifier.scopusid2-s2.0-0033879063-
dc.type.rimsART-
dc.citation.volume21-
dc.citation.issue2-
dc.citation.beginningpage93-
dc.citation.endingpage105-
dc.citation.publicationnamePATTERN RECOGNITION LETTERS-
dc.contributor.localauthorBien, Zeung nam-
dc.contributor.nonIdAuthorPark, GT-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorfuzzy observer-
dc.subject.keywordAuthorfuzzy neural network-
dc.subject.keywordAuthorfacial analysis-
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