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undergraduate thesis
Duboko učenje za vizualnu odometriju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:054946
Lončar, Jelena
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Lončar, J. (2024). Duboko učenje za vizualnu odometriju (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:054946

Lončar, Jelena. "Duboko učenje za vizualnu odometriju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:054946

Lončar, Jelena. "Duboko učenje za vizualnu odometriju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:054946

Lončar, J. (2024). 'Duboko učenje za vizualnu odometriju', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:054946

Lončar J. Duboko učenje za vizualnu odometriju [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:054946

J. Lončar, "Duboko učenje za vizualnu odometriju", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:054946

Metadata
TitleDuboko učenje za vizualnu odometriju
Title (english)Deep learning for visual odometry
AuthorJelena Lončar
MentorIvan Marković (mentor)
Committee memberIvan Marković (član povjerenstva)
Committee memberMarta Čolaković-Bencerić (član povjerenstva)
Committee memberVlaho-Josip Štironja (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Rad istražuje implementaciju i evaluaciju sustava vizualne odometrije temeljenog na dubokom učenju, poznatog kao DeepVO. Vizualna odometrija ključna je značajka za praćenje kretanja kamere u stvarnom vremenu. Naglasak je na integraciji dubokih neuronskih mreža u svrhu poboljšanja preciznosti i robusnosti odometrijskog sustava automatskim ekstrahiranjen složenih značajki iz vizualnih podataka. Pomoću detaljno opisanih metodoloških pristupa, predočava se arhitektura DeepVO sustava, implementirana putem PyTorch okvira za duboko učenje. Evaluacija performansi izvršena je na relevantnim skupovima podataka koja zaključuje rad diskusijom o postignutim rezultatima i mogućim smjerovima budućih istraživanja.
Abstract (english)
The paper analyzes the implementation and evaluation of the visual odometry system based on deep learning, also known as DeepVO. Visual odometry is the key component for tracking videocamera movement in real time. The emphasis is on the integration of deep neural networks which improve the precision and robustness of odometric systems by automatically extracting complex features from visual data. Using detailed methodological approaches, the architecture of the DeepVO system, implemented through the PyTorch framework for deep learning, is presented. The benchmark testing is performed on the relevant data sets. It concludes the paper with a discussion of the results achieved and possible directions for future research.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:054946
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 on2024-10-12 21:20:24