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dc.contributor.advisorSeguí Mesquida, Santi-
dc.contributor.authorPascual, Guillem-
dc.descriptionTreballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Santi Seguí Mesquidaca
dc.description.abstractColorizing is the act of giving color to grayscale images. A convolutional-neural-network-based method to colorize images without human interaction is presented in this project. Various frameworks, architectures, color spaces and approximations are explored to obtain the final model, capable of correctly restoring the original color of photographies without any further information than the image itself. The principal aim of this project is to propose an idempotent architecture that could be trained with all kinds of images and yet produce good results. To demonstrate how the process works and show the obtained results, three categories of images will be used along this project: synthetic images representing numbers, landscape images and human
dc.format.extent61 p.-
dc.rightsmemòria: cc-by-nc-sa (c) Guillem Pascual Guinovart, 2016-
dc.rightscodi: GPL (c) Guillem Pascual Guinovart, 2016-
dc.subject.classificationXarxes neuronals (Informàtica)cat
dc.subject.classificationAprenentatge automàticcat
dc.subject.classificationTreballs de fi de graucat
dc.subject.classificationProcessament digital d'imatgesca
dc.subject.classificationMineria de dadesca
dc.subject.otherNeural networks (Computer science)eng
dc.subject.otherMachine learningeng
dc.subject.otherComputer softwareeng
dc.subject.otherBachelor's thesiseng
dc.subject.otherDigital image processingeng
dc.subject.otherData miningeng
dc.titleAutomatic image colorizationca
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica
Programari - Treballs de l'alumnat

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