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dc.contributor.advisorDornaika, Fadi
dc.contributor.advisorArganda Carreras, Ignacio
dc.contributor.authorRoa Barco, Leire
dc.date.accessioned2018-09-11T06:59:31Z
dc.date.available2018-09-11T06:59:31Z
dc.date.issued2017-12-20
dc.identifier.urihttp://hdl.handle.net/10810/28643
dc.description.abstractThis master thesis compares different face descriptors using classification techniques in order to classify emotions in images of faces of people of different ethnicities and ages, male and female. The comparison is done between hand-crafted features such as LBP and HOG and more modern features such as some pre-trained neural networks. The proposed methods were used on different databases, using different image sizes and cropping and standardizing all the images. The experimental results showed that some of the hand- crafted features were better that the pre-trained neural networks. To facilitate replication of our experiments the MATLBAB source code will be available at https://github. com/nagwlei/FaceEmotions .es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subjectface imagees_ES
dc.subjectclassificationes_ES
dc.subjectneural networkes_ES
dc.titleAnalysis of facial expressions: experiments on multiple databaseses_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
dc.rights.holderAtribución-NoComercial-CompartirIgual 3.0 Españaes_ES


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Atribución-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Atribución-NoComercial-CompartirIgual 3.0 España