Utilize este identificador para referenciar este registo: https://hdl.handle.net/10216/88482
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dc.creatorJohn Michael Salgado Cebola
dc.date.accessioned2025-11-10T18:54:58Z-
dc.date.available2025-11-10T18:54:58Z-
dc.date.issued2016-07-19
dc.date.submitted2016-07-29
dc.identifier.othersigarra:170137
dc.identifier.urihttps://hdl.handle.net/10216/88482-
dc.descriptionComparative study between the performance of Convolutional Networks using pretrained models and statistical generative models on tasks of image classification in semi-supervised enviroments. Study of multiple ensembles using these techniques and generated data from estimated pdfs. Pretrained Convents, LDA, pLSA, Fisher Vectors, Sparse-coded SPMs, TSVMs being the key models worked upon.
dc.language.isopor
dc.rightsopenAccess
dc.subjectEngenharia electrotécnica, electrónica e informática
dc.subjectElectrical engineering, Electronic engineering, Information engineering
dc.titlePre-trained Convolutional Networks and generative statiscial models: a study in semi-supervised learning
dc.typeDissertação
dc.contributor.uportoFaculdade de Engenharia
dc.identifier.doi10.34626/ars2-pp29
dc.identifier.tid201309084
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
thesis.degree.disciplineMestrado Integrado em Engenharia Electrotécnica e de Computadores
thesis.degree.grantorFaculdade de Engenharia
thesis.degree.grantorUniversidade do Porto
thesis.degree.level1
Aparece nas coleções:FEUP - Dissertação

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