Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža

Ćaleta, Mislav

master's thesis

Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža

Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. urn:nbn:hr:200:323810

Ćaleta, Mislav

Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Institutional repository: Faculty of Electrical Engineering, Computer Science and Information Technology Osijek

Cite this document

APA 6th Edition

Ćaleta, M. (2023). Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:323810

MLA 8th Edition

Ćaleta, Mislav. "Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:323810

Chicago 17th Edition

Harvard

Ćaleta, M. (2023). 'Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 22 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:323810

Vancouver

Ćaleta M. Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2024 May 22] Available at: https://urn.nsk.hr/urn:nbn:hr:200:323810

IEEE

M. Ćaleta, "Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:323810

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:323810

Metadata

Title	Generiranje umjetnih slika lica pomoću generativnih suparničkih mreža
Title (english)	Generating Synthetic Images of Human Faces by Generative Adversarial Networks
Author	Mislav Ćaleta
Mentor	Robert Cupec (mentor)
Committee member	Robert Cupec (predsjednik povjerenstva)
Committee member	Ratko Grbić (član povjerenstva)
Committee member	Emmanuel Karlo Nyarko (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek (Department of Computer Engineering and Automation) (Chair of Automation and Robotics) Osijek
Defense date and country	2023-09-14, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Artificial Intelligence
Abstract	Glavni zadatak rada je bio napraviti model suparničkih generativnih mreža čija će generatorska mreža nakon učenja uspješno generirati slike ljudskih lica. Na početku je objašnjena sva potrebna teorija za shvaćanje modela koji su u radu napravljeni i korišteni. Nakon toga je prikazana potrebna priprema za sam proces izgradnje modela i njihovog učenja. Na kraju su svi modeli objašnjeni i pojašnjeni su razlozi za promjene koje su napravljene na modelima da bi se dobili bolji rezultati. Također su prikazani rezultati i objašnjeni su nedostatci rezultata i kako pristupiti poboljšanju. Poboljšanja koja su primijenjena u radu kako bi se postigli željeni rezultati proizlaze iz teorije strojnog učenja, točnije metoda iz dubokog učenja koje su se pokazale kao dobre metode za rješavanje problema koji se pojavljuju kroz rad. Svako poboljšanje je objašnjeno i naveden je jasan razlog zašto je napravljeno i kako bi teoretski trebalo utjecati na rezultate modela. Budući da su slike kroz verzije modela znatno bolje može se zaključiti da ovi postupci nisu učinkoviti samo u teoriji već su pomogli u generiranju kvalitetnijih slika.
Abstract (english)	The main task of this paper was to create a model of adversarial generative networks whose generator network after learning will successfully generate images of human faces. At the beginning, all the necessary theory for understanding the models that were created and used in the paper was explained. After that, the necessary preparation for the process of building the models and their learning is presented. At the end, all models are explained and the reasons for the changes made to the models for the purpose of getting the better results are clarified. The results are also presented. The shortcomings of the results and how to approach the improvements are explained. The improvements that have been applied in this paper to achieve the desired results stem from machine learning theory, more specifically deep learning methods that have proven to be good methods for solving problems that arise through this work. Each improvement is explained and a clear reason is given why it was made and how it should theoretically affect the results of the model. Because the images with different model versions are significantly better it can be concluded that these procedures are not efficient only in theory but also that they helped to generate higher quality images.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:200:323810
Study programme	Title: Graduate University Study Programme in Computer Engineering Study programme type: university Study level: graduate Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
Terms of use
Created on	2023-10-02 11:20:49

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