TripletGAN: model for image generation

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dc.contributor.advisorSeguí Mesquida, Santi
dc.contributor.authorDomínguez Mira, Ricardo
dc.date.accessioned2019-06-21T08:33:25Z
dc.date.available2019-06-21T08:33:25Z
dc.date.issued2019-01-18
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2019, Director: Santi Seguí Mesquidaca
dc.description.abstract[en] Generative Adversarial Networks (GANs) have been widely used for image generation. From the conception of this model in 2014 until now, there has been a increasingly interest in this model, which have lead it to be one of the most popular Deep Learning models nowadays. The popularity of this model has entailed a significant list of variations of it. This work aims are to study the GAN model, and specifically, one of its variations: TripletGAN.ca
dc.format.extent59 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/135720
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Ricardo Domínguez Mira, 2019
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques
dc.subject.classificationAprenentatge automàticca
dc.subject.classificationTreballs de fi de grau
dc.subject.classificationResolució de problemesca
dc.subject.classificationSistemes d'imatgesca
dc.subject.classificationAlgorismes computacionalsca
dc.subject.otherMachine learningen
dc.subject.otherBachelor's theses
dc.subject.otherProblem solvingen
dc.subject.otherImaging systemsen
dc.subject.otherComputer algorithmsen
dc.titleTripletGAN: model for image generationca
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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