Fabrizio Lande
Multimodal-source image generation with deep learning.
Rel. Paolo Garza, Erfan Ghaderey, Ruben Cartuyvels Cartuyvels. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2021
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| Abstract: |
The focus of this work almost completely carried on during my stay at KU Leuven University as part of my Erasmus project, is to present a new way of synthesizing images starting from a descriptive input text and a reference image by using a model, RaGAN, extensively based on deep learning and generative adversarial network, that could set a base for future experimentation in this hybrid field that is multimodal source image generation. |
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| Relatori: | Paolo Garza, Erfan Ghaderey, Ruben Cartuyvels Cartuyvels |
| Anno accademico: | 2021/22 |
| Tipo di pubblicazione: | Elettronica |
| Numero di pagine: | 80 |
| Soggetti: | |
| Corso di laurea: | Corso di laurea magistrale in Data Science And Engineering |
| Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA |
| Ente in cotutela: | KUL - KATHOLIEKE UNIVERSITEIT LEUVEN (BELGIO) |
| Aziende collaboratrici: | Ku Leuven |
| URI: | http://webthesis.biblio.polito.it/id/eprint/21219 |
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