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master's thesis
Vrednovanje tehnika rastresanja podataka za konvolucijske modele
2020. urn:nbn:hr:168:839427
Kraševac, Natko
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Kraševac, N. (2020). Vrednovanje tehnika rastresanja podataka za konvolucijske modele (Master's thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:839427

Kraševac, Natko. "Vrednovanje tehnika rastresanja podataka za konvolucijske modele." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:839427

Kraševac, Natko. "Vrednovanje tehnika rastresanja podataka za konvolucijske modele." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:839427

Kraševac, N. (2020). 'Vrednovanje tehnika rastresanja podataka za konvolucijske modele', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 March 2023, https://urn.nsk.hr/urn:nbn:hr:168:839427

Kraševac N. Vrednovanje tehnika rastresanja podataka za konvolucijske modele [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2023 March 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:839427

N. Kraševac, "Vrednovanje tehnika rastresanja podataka za konvolucijske modele", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:839427

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Metadata
TitleVrednovanje tehnika rastresanja podataka za konvolucijske modele
Title (english)Evaluation of jittering techniques for convolutional models
AuthorNatko Kraševac
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberŽeljka Mihajlović (član povjerenstva)
Committee memberTomislav Hrkać (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Duboki konvolucijski modeli su glavni sastojak mnogih praktičnih primjena računalnog vida. Međutim, takvi modeli su ponekad nepraktični jer zahtijevaju velike skupove označenih podataka za učenje. Zbog toga postupci za rastresanje podataka predstavljaju zanimljivo područje istraživanja. U okviru ovog rada proučene su i implementirane metode za rastresanje podataka. Provedeni su eksperimenti i svaka od metoda je vrednovana i uspoređena s rezultatima iz literature.
Abstract (english)
Deep convolutional models are the main instrument for many practical applications in the field of computer vision. However, these models are sometimes unpractical because they require great amounts of training data. Therefore, jittering and augmentation techniques impose themselves as interesting filed for reasearch. In this thesis, some of the recent techniques were researched and implemented. Experiments were conducted and each technique was evaluated and compared to results from the literature.,
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:839427
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
Access conditionsClosed access
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Created on2023-01-13 10:12:43