prikaz prve stranice dokumenta Interpretiranje diskriminativnih konvolucijskih modela
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master's thesis
Interpretiranje diskriminativnih konvolucijskih modela
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:980572
Ceraj, Tin
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Ceraj, T. (2020). Interpretiranje diskriminativnih konvolucijskih modela (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:980572

Ceraj, Tin. "Interpretiranje diskriminativnih konvolucijskih modela." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:980572

Ceraj, Tin. "Interpretiranje diskriminativnih konvolucijskih modela." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:980572

Ceraj, T. (2020). 'Interpretiranje diskriminativnih konvolucijskih modela', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:980572

Ceraj T. Interpretiranje diskriminativnih konvolucijskih modela [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 June 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:980572

T. Ceraj, "Interpretiranje diskriminativnih konvolucijskih modela", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:980572

Metadata
TitleInterpretiranje diskriminativnih konvolucijskih modela
Title (english)Interpreting discriminative convolutional models
AuthorTin Ceraj
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberSlobodan Ribarić (član povjerenstva)
Committee memberVlado Glavinić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Interpretiranje dubokih konvolucijskih modela je bitno za njihovo korištenje u industriji kako ne bi došlo do neočekivanih tj. neželjenih ishoda. U ovom radu se proučavaju i testiraju metode za interpretaciju modela. Metode obuhvaćene ovim radom vizualiziraju modele generiranjem slika korišenjem znanja modela. Pokazano je da napredne metode generiraju realistične slike i da korišteni modeli ne uče samo jednostavne značajke, već da mogu razaznati klase kao cjeline koje i čovjek vidi. U eksperimentima je pokazano da su robusni modeli još bolji u tome, odnosno da oni razaznaju značajke na višoj razini od nerobusnih modela. Pokazani su rezultati eksperimenata i predloženi budući pravci razvoja.
Abstract (english)
Interpretation of deep convolutional models is essential for their use in industry in order to avoid unexpected, i.e. undesirable outcomes. This paper focuses on methods for interpreting models and test them. The methods covered in this paper are used to visualize a model by generating images using the model knowledge. It has been shown that advanced methods generate realistic images and that the models used not only learn simple features but that they can distinguish classes as wholes in a similar way a human can. Experiments have shown that robust models are even better at this, that they recognize features at a higher level than non-robust models. The results of the experiments are shown and future directions of development are suggested.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:980572
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 09:50:36