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dc.contributor.author | Mykhailych, Mykola![]() |
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dc.date.accessioned | 2018-01-25T18:24:33Z | |
dc.date.available | 2018-01-25T18:24:33Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Mykhailych, Mykola. Application of Generative Neural Models for Style Transfer Learning in Fashion : Master Thesis : manuscript / Mykola Mykhailych ; Supervisor Dr. Rostyslav Hryniv ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2017. – 63 p. : ill. | uk |
dc.identifier.uri | http://er.ucu.edu.ua/handle/1/1190 | |
dc.description.abstract | The purpose of this thesis is to analyze different generative adversarial networks for application in fashion. Research of “mode collapse” problem of generative adversarial networks. We studied the theoretical part of the “mode collapse” and conducted experiments on a synthetic toy dataset, and a dataset containing real data from fashion. Due to the developed method, it was possible to achieve visible results of improving the quality of garment generation by solving the problem of collapse. | uk |
dc.language.iso | en | uk |
dc.subject | Generative modeling | uk |
dc.subject | GAN framework | uk |
dc.subject | Datasets | uk |
dc.subject | Pix2pix framework | uk |
dc.title | Application of Generative Neural Models for Style Transfer Learning in Fashion | uk |
dc.type | Preprint | uk |
dc.status | Публікується вперше | uk |