prikaz prve stranice dokumenta Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom
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undergraduate thesis
Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:456628
Babić, Dominik
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Babić, D. (2023). Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:456628

Babić, Dominik. "Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:456628

Babić, Dominik. "Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:456628

Babić, D. (2023). 'Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:456628

Babić D. Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 November 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:456628

D. Babić, "Varijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:456628

Metadata
TitleVarijacijski autoenkoderi s kvantiziranom latentnom reprezentacijom
Title (english)Variational autoencodets with quantized latent representation
AuthorDominik Babić
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberIvan Grubišić (član povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zadatak ovog rada je bio uvod u osnovne pojmove i koncepte VQ-VAE modela te uspostaviti vezu s već definiranim varijacijskim autoenkoderima. Uz to, cilj je bio predstaviti osnovne matematičke izvode za definiranje VQ-VAE modela, kao što su varijacijska inferencija, rekonstrukcijski gubitak, regularizacijski gubitak i gubitak kvantizacije. Zatim je provedeno izvod̄enje varijacijskih autoenkodera i VQ-VAE modele te njihovo treniranje na jednostavnijem skupu slika (konkretno, MNIST slika znamenki) kako bi se istražila njihova sposobnost rekonstrukcije slika. Takod̄er je bilo potrebno odabrati odred̄enu javno dostupnu prednaučenu arhitekturu i provesti ispitivanje nad njom. Potom su prikazani dobiveni rezultati provedenih ispitivanja te su izvedeni zaključci o performansama ispitanih arhitektura.
Abstract (english)
This study aimed to provide an introduction to the fundamental concepts and principles of the VQ-VAE model and establish a connection with the already defined variational autoencoders. Additionally, the goal was to present the basic mathematical derivations for defining the VQ-VAE model, such as variational inference, reconstruction loss, regularization loss, and quantization loss. Furthermore, variational autoencoders and VQ-VAE models were derived and trained on a more specific dataset of images (specifically, MNIST digit images) to explore their ability to reconstruct images. It was also necessary to select a specific publicly available pre-trained architecture and evaluate it. Subsequently, the obtained results of the conducted evaluations were presented, and conclusions were drawn regarding the performance of the examined architectures.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:456628
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-07-13 09:53:13