Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/67209
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dc.contributor.advisorSeguí Mesquida, Santi-
dc.contributor.authorMartínez, Pablo (Martínez Martínez)-
dc.date.accessioned2015-10-09T07:44:16Z-
dc.date.available2015-10-09T07:44:16Z-
dc.date.issued2015-06-27-
dc.identifier.urihttp://hdl.handle.net/2445/67209-
dc.descriptionTreballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2015, Director: Santi Seguí Mesquidaca
dc.description.abstractCapsule endoscopy is a diagnostic technique that opens a wide field of research in the clinical area. Through the capsule, videos of the entire digestive tract can be obtained, as it is ingested by the patient. There are many projects related to the data extraction of these videos, one of them, a Convolutional Deep Neural Network which is able to classify images of the small intestine in six different classes. Nevertheless, since the v ́ıdeo is obtained until it's able to be processed by the Convolutional Deep Neural Network, a set of operations are needed. In the first part of this document, an approach to get this work done is proposed. In the second part, the results of the neural network are used to create an application that tries to find sequences in videos and segment the videos based on that sequences.ca
dc.format.extent59 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isospaca
dc.rightsmemòria: cc-by-nc-sa (c) Pablo Martínez Martínez, 2015-
dc.rights.urihttp://creativecommons.org/licenses/by-sa/3.0/es-
dc.sourceTreballs Finals de Grau (TFG) - Enginyeria Informàtica-
dc.subject.classificationVisió per ordinadorcat
dc.subject.classificationReconeixement de formes (Informàtica)cat
dc.subject.classificationProgramaricat
dc.subject.classificationTreballs de fi de graucat
dc.subject.classificationProcessament digital d'imatgesca
dc.subject.classificationCàpsula endoscòpicaca
dc.subject.classificationMotilitat gastrointestinalca
dc.subject.classificationXarxes neuronals (Informàtica)ca
dc.subject.otherComputer visioneng
dc.subject.otherPattern recognition systemseng
dc.subject.otherComputer softwareeng
dc.subject.otherBachelor's theseseng
dc.subject.otherDigital image processingeng
dc.subject.otherCapsule endoscopyeng
dc.subject.otherGastrointestinal motilityeng
dc.subject.otherNeural networks (Computer science)eng
dc.titleAnálisis de la motilidad intestinal utilizando Convolutional Deep Neural Network y la cápsula endoscópicaca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Enginyeria Informàtica

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