A novel feature selection for fuzzy neural networks for personalized facial expression recognition

Cited 4 time in webofscience Cited 0 time in scopus
  • Hit : 325
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorKim, DJko
dc.contributor.authorBien, Zeung namko
dc.date.accessioned2013-03-06T05:28:14Z-
dc.date.available2013-03-06T05:28:14Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2004-06-
dc.identifier.citationIEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, v.E87A, pp.1386 - 1392-
dc.identifier.issn0916-8508-
dc.identifier.urihttp://hdl.handle.net/10203/85953-
dc.description.abstractThis paper proposes a novel feature selection method for the fuzzy neural networks and presents an application example for 'personalized' facial expression recognition. The proposed method is shown to result in a superior performance than many existing approaches.-
dc.languageEnglish-
dc.publisherIEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG-
dc.titleA novel feature selection for fuzzy neural networks for personalized facial expression recognition-
dc.typeArticle-
dc.identifier.wosid000221983900015-
dc.identifier.scopusid2-s2.0-3042638298-
dc.type.rimsART-
dc.citation.volumeE87A-
dc.citation.beginningpage1386-
dc.citation.endingpage1392-
dc.citation.publicationnameIEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES-
dc.contributor.localauthorBien, Zeung nam-
dc.contributor.nonIdAuthorKim, DJ-
dc.type.journalArticleArticle; Proceedings Paper-
dc.subject.keywordAuthorpersonalized facial expression recognition-
dc.subject.keywordAuthorfeature selection-
dc.subject.keywordAuthorfuzzy neural networks-
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 4 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0