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master's thesis
Duboko učenje za procjenu kvalitete šahovskih pozicija
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:938811
Giljanović, Luka
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Giljanović, L. (2022). Duboko učenje za procjenu kvalitete šahovskih pozicija (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:938811

Giljanović, Luka. "Duboko učenje za procjenu kvalitete šahovskih pozicija." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:938811

Giljanović, Luka. "Duboko učenje za procjenu kvalitete šahovskih pozicija." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:938811

Giljanović, L. (2022). 'Duboko učenje za procjenu kvalitete šahovskih pozicija', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:938811

Giljanović L. Duboko učenje za procjenu kvalitete šahovskih pozicija [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 July 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:938811

L. Giljanović, "Duboko učenje za procjenu kvalitete šahovskih pozicija", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:938811

Metadata
TitleDuboko učenje za procjenu kvalitete šahovskih pozicija
Title (english)Deep Learning for Evaluation of Chess Positions
AuthorLuka Giljanović
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberMirko Poljak (član povjerenstva)
Committee memberTomislav Marković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog rada bio je istražiti kako evaluirati šahovsku poziciju pomoću dubokog učenja. Na početku rada iznesena je problematika evaluacije šahovske pozicije. U prvom dijelu rada opisuje se kako su se prikupljali podatci koji su kasnije korišteni u izgradnji modela. U drugom dijelu rada opisano je kako su se podatci pripremili, odnosno kako su se prilagodili za učenje modela konvolucijske neuronske mreže. U trećem dijelu rada prikazana je izgradnja modela i objašnjena je njegova arhitektura. Konačno, prikazani su rezultati testiranja modela.
Abstract (english)
The aim of this paper was to explore how to evaluate a chess position using deep learning. At the beginning of the paper, the issue of evaluation of the chess position was presented. The first part of the paper describes how the data, that were later used in building the model, were collected. The second part of the paper describes how the data were prepared, ie how they were adapted for convolutional neural network model. The third part of the paper presents the construction of the model and explains its architecture. Finally, the test results of the model are presented.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:938811
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 on2023-01-14 08:48:41