Investigating Single Translation Function CycleGANs

Olmucci Poddubnyy, Oleksandr (2018) Investigating Single Translation Function CycleGANs. [Laurea], Università di Bologna, Corso di Studio in Informatica [L-DM270]
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Abstract

With the advent of Deep Learning, we have been able to find solutions to many problems which didn't have an algorithmic solution, among these the image-to-image translation problem. One approach to solve it is by using the CycleGAN framework, which allows to learn mappings between two given image categories (or classes) that aren't necessarily paired. In this dissertation we present some attempts that were done in order to use the CycleGAN approach to perform image translations between more than two image classes at a time.

Abstract
Tipologia del documento
Tesi di laurea (Laurea)
Autore della tesi
Olmucci Poddubnyy, Oleksandr
Relatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
deep learning,python,tensorflow,GAN,CNN,CycleGAN
Data di discussione della Tesi
18 Luglio 2018
URI

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