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master's thesis
Generiranje slika generativnim suparničkim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:312068
Zebić, Bruno
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Zebić, B. (2021). Generiranje slika generativnim suparničkim mrežama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:312068

Zebić, Bruno. "Generiranje slika generativnim suparničkim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:312068

Zebić, Bruno. "Generiranje slika generativnim suparničkim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:312068

Zebić, B. (2021). 'Generiranje slika generativnim suparničkim mrežama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 01 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:312068

Zebić B. Generiranje slika generativnim suparničkim mrežama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 June 01] Available at: https://urn.nsk.hr/urn:nbn:hr:168:312068

B. Zebić, "Generiranje slika generativnim suparničkim mrežama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:312068

Metadata
TitleGeneriranje slika generativnim suparničkim mrežama
Title (english)Generating Images Using Generative Adversarial Networks
AuthorBruno Zebić
MentorTomislav Hrkać (mentor)
Committee memberTomislav Hrkać (predsjednik povjerenstva)
Committee memberZoran Kalafatić (član povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-16, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U okviru ovog rada proučeni su najznačajniji generativni suparnički učeni modeli opisani u literature i programski je ostvaren takav sustav temeljen na prikladnom modelu i uz korištenje prikladnih biblioteka. Proučena su četiri značajna generativna suparnička modela i jedan od njih je odabran kao prikladan model za ostvarivanje zadatka. Pripremljena je baza slika realističnih fotografija lica ljudi na kojima bi se sustav mogao učiti i ispitivati. Sustav je zatim implementiran. Njegovi rezultati su analizirani i prikazani grafički. Rezultat je takav da je dio slika uspješno imitirao fotografije realističnih slika ljudi.
Abstract (english)
Within this paper, the most significant generative adversarial learning models described in the literature were studied and such a system based on a suitable model and with the use of appropriate libraries was programmatically realized. Four significant generative adversarial models were studied and one of them was selected as a suitable model for accomplishing the task. A database of images of realistic photographs of people's faces has been prepared on which the system could be learned and tested. The system is then implemented. Its results were analyzed and presented graphically. The result is such that some of the images successfully mimicked photographs of realistic images of people.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:312068
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 on2023-01-13 14:17:42