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dc.contributor.advisorMolina Soriano, Rafael 
dc.contributor.advisorKatsaggelos, Aggelos K.
dc.contributor.authorLópez Tapia, Santiago
dc.contributor.otherUniversidad de Granada. Programa de Doctorado en Tecnologías de la Información y la Comunicaciónes_ES
dc.date.accessioned2021-02-12T09:31:50Z
dc.date.available2021-02-12T09:31:50Z
dc.date.issued2021
dc.date.submitted2021-01-29
dc.identifier.citationLópez Tapia, Santiago. Modelos de Aprendizaje Profundo para el Procesamiento y Clasificación de Imágenes y Vídeo. Granada: Universidad de Granada, 2021. [http://hdl.handle.net/10481/66493]es_ES
dc.identifier.isbn9788413067605
dc.identifier.urihttp://hdl.handle.net/10481/66493
dc.descriptionThe work of Santiago López-Tapia and Rafael Molina was supported by the the Spanish Ministry of Economy and Competitiveness through project DPI2016-77869-C2-2-R and the Visiting Scholar program at the University of Granada. Santiago López-Tapia received financial support through the Spanish FPU programes_ES
dc.description.abstractMotivated by the success of DL-based models in image and video problems, in this dissertation, we develop DL-models for challenging image and video formation and interpretation tasks. These are image and video SR, BID, threat detection in PMMWIs and mitosis detection in Whole-Slide Images (WSIs). In this thesis, one common point to all contributions is the use of domain knowledge to improve the solution by developing and applying specialized architectures, regularizations and restrictions. In the next subsections, we present the tasks that we have addressed in this dissertation. Next, we provide a brief introduction to the main DL-based models used in this dissertation: CNNs and Generative Adversarial Networks (GANs). Finally, we present the objectives of this work and the structure of the remainder of this dissertation.es_ES
dc.description.sponsorshipTesis Univ. Granada.es_ES
dc.description.sponsorshipSpanish Ministry of Economy and Competitiveness through project DPI2016-77869-C2-2-R and the Visiting Scholar program at the University of Granadaes_ES
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenges_ES
dc.publisherUniversidad de Granadaes_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectDeep learninges_ES
dc.subjectImage processing es_ES
dc.subjectVideo processinges_ES
dc.titleModelos de Aprendizaje Profundo para el Procesamiento y Clasificación de Imágenes y Vídeoes_ES
dc.title.alternativeDeep Learning Models for Image and Video Processing and Classificationes_ES
dc.typeinfo:eu-repo/semantics/doctoralThesises_ES
europeana.typeTEXTen_US
europeana.dataProviderUniversidad de Granada. España.es_ES
europeana.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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