Emotion classification using hidden layer outputs

dc.authorscopusid55364395900
dc.authorscopusid6506642154
dc.contributor.authorGünler,M.A.
dc.contributor.authorTora,H.
dc.contributor.otherAirframe and Powerplant Maintenance
dc.date.accessioned2024-07-05T15:43:49Z
dc.date.available2024-07-05T15:43:49Z
dc.date.issued2012
dc.departmentAtılım Universityen_US
dc.department-tempGünler M.A., Data Communication Department, Vakiflar Bankasi T.A.O EBIS, Ankara, Turkey; Tora H., Electrical and Electronics Engineering Department, Atilim University, Ankara, Turkeyen_US
dc.description.abstractNeural network (NN) with Multi-Layer Perceptron (MLP) is a supervised learning algorithm composed of artificial neurons. Multilayer NN is capable of solving nonlinear classification problems such as emotion identification by using facial expressions that is presented in this paper. Hidden layer outputs of NN provide useful information about facial appearance. This study addresses that without fully training NN hidden layer outputs can be used as feature. It is shown that an acceptable recognition rate is obtained by means of hidden layer outputs. © 2012 IEEE.en_US
dc.identifier.citation3
dc.identifier.doi10.1109/INISTA.2012.6247027
dc.identifier.isbn978-146731446-6
dc.identifier.scopus2-s2.0-84866604175
dc.identifier.urihttps://doi.org/10.1109/INISTA.2012.6247027
dc.identifier.urihttps://hdl.handle.net/20.500.14411/3668
dc.institutionauthorTora, Hakan
dc.language.isoenen_US
dc.relation.ispartofINISTA 2012 - International Symposium on INnovations in Intelligent SysTems and Applications -- International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2012 -- 2 July 2012 through 4 July 2012 -- Trabzon -- 92831en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfacial expressionsen_US
dc.subjectimage processingen_US
dc.subjectMulti layer neural networken_US
dc.titleEmotion classification using hidden layer outputsen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
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