Reconstructing Images and Audio: Multi-modal autoencoders

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dc.contributor.advisorLanillos Pradas, P. L.
dc.contributor.authorvan der Linden, N. R. L.
dc.date.issued2020-07-01
dc.description.abstractIn this thesis, a multi-modal auto-encoder is built that reconstructs both images and audio. The goal is to build a multi-modal auto-encoder that is capable of learning a shared representation between images of digits and audio of the pronunciation of the digits. This model, while fairly accurate on digits, does not perform very well on the audio data.en_US
dc.embargo.lift10000-01-01
dc.embargo.typePermanent embargoen_US
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/12733
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleReconstructing Images and Audio: Multi-modal autoencodersen_US
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