Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/170970
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dc.contributor.advisorLuri Carrascoso, Xavier-
dc.contributor.authorAguasca Cabot, Arnau-
dc.date.accessioned2020-09-30T12:12:27Z-
dc.date.available2020-09-30T12:12:27Z-
dc.date.issued2020-06-
dc.identifier.urihttp://hdl.handle.net/2445/170970-
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2020. Tutor: Francesc Xavier Luri Carrascosoca
dc.description.abstractA study of the implementation of deep learning using artificial neural networks is undertaken aiming to reduce processing time and human supervision in the characterization of exoplanets’ light curves. Firstly, to understand the problem and the techniques involved, a convolutional neural network proposed by Shallue & Vanderburg for the Kepler mission is studied and recreated. Secondly, different alternative neural networks are proposed and compared with the original one, aiming to improve the classification performanceca
dc.format.extent5 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Aguasca, 2020-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física-
dc.subject.classificationPlanetes extrasolarscat
dc.subject.classificationXarxes neuronals (Informàtica)cat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherExtrasolar planetseng
dc.subject.otherNeural networks (Computer science)eng
dc.subject.otherBachelor's theseseng
dc.titleCharacterization of exoplanets' light curves with neural networks-
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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