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dc.contributor.authorStoean, Catalin
dc.date.accessioned2019-04-18T09:15:04Z
dc.date.available2019-04-18T09:15:04Z
dc.date.created2019
dc.date.issued2019-04-18
dc.identifier.urihttps://hdl.handle.net/10630/17530
dc.description.abstractThis hands-on presentation will be focused on practical, essential aspects that are necessary in order to build a custom classifier. The tutorial will start from prerequisites, like the libraries that are necessary to install, to the step-by-step procedure for classifying new classes, which have not been previously learnt, by a pre-trained model using transfer learning. Such a separation of new classes of objects in images starts with the building of the novel image data set, its separation into training, validation and test sets. The model will learn to distinguish the objects from the images in the training set, it will be tuned on a validation set and finally it will face images from the previously unseen test set.en_US
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Techen_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAprendizaje automático (Inteligencia artificial)en_US
dc.subject.otherClassificationen_US
dc.subject.otherDeep Learningen_US
dc.subject.otherAprendizaje profundoen_US
dc.titleOn classifying images using Keras and Tensorflow in Pythonen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.centroE.T.S.I. Telecomunicaciónen_US
dc.relation.eventdateJunio 2019en_US


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