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master's thesis
Stvaranje slika pomoću dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:810541
Rezić, Ivan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Rezić, I. (2019). Stvaranje slika pomoću dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:810541

Rezić, Ivan. "Stvaranje slika pomoću dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:810541

Rezić, Ivan. "Stvaranje slika pomoću dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:810541

Rezić, I. (2019). 'Stvaranje slika pomoću dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 01 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:810541

Rezić I. Stvaranje slika pomoću dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 June 01] Available at: https://urn.nsk.hr/urn:nbn:hr:168:810541

I. Rezić, "Stvaranje slika pomoću dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:810541

Metadata
TitleStvaranje slika pomoću dubokog učenja
Title (english)Generating Images Using Deep Learning
AuthorIvan Rezić
MentorMarin Šilić (mentor)
Committee memberMarin Šilić (predsjednik povjerenstva)
Committee memberSiniša Srbljić (član povjerenstva)
Committee memberGoran Delač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zbog svog potencijala, nenadzirano učenje jako je važno područje strojnog učenja. Ono nam omogućuje iskorištavanje velike količine neoznačenih podataka. U ovom radu bavimo se modelima nenadziranog učenja. U uvodnim poglavljima opisani su sastavni dijelovi dubokih modela. Dan je pregled postojećih generativnih modela, a poseban fokus bio je na generativne suparničke modele za stvaranje slika. Predstavljena su četiri modela za stvaranje slika i jedan model za povećavanje rezolucije slika te su implementirani korištenjem biblioteke Keras. Na kraju su prikazani i opisani dobiveni rezultati nad Fashion MNIST i DIV2K podatkovnim skupovima.
Abstract (english)
Because of its potential, unsupervised learning is a very important field of machine learning. It allows us exploiting large amounts of unlabeled data. In this paper we are dealing with models of unsupervised learning. The introductory chapters describe the component parts of deep models. There was given an overview of existing generative models, with emphasis on generative adversarial models for image generation. Four image-creation models and one image-enhancing model were introduced and implemented using library Keras. Finally, in the lasts parts of paper the results over the Fashion MNIST and DIV2K data sets are shown and described.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:810541
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2020-01-07 21:50:29