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undergraduate thesis
Sustav za raspoznavanje prometnih znakova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:455537
Galić, Luka
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Galić, L. (2023). Sustav za raspoznavanje prometnih znakova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:455537

Galić, Luka. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:455537

Galić, Luka. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:455537

Galić, L. (2023). 'Sustav za raspoznavanje prometnih znakova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 10 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:455537

Galić L. Sustav za raspoznavanje prometnih znakova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 August 10] Available at: https://urn.nsk.hr/urn:nbn:hr:168:455537

L. Galić, "Sustav za raspoznavanje prometnih znakova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:455537

Metadata
TitleSustav za raspoznavanje prometnih znakova
Title (english)System for traffic sign recognition
AuthorLuka Galić
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberHrvoje Nuić (član povjerenstva)
Committee memberZorana Doždor (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-03, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zadatak ovog završnog rada je programski ostvariti sustav za raspoznavanje prometnih znakova u slikama snimljenim iz vozila u pokretu i ispitati ponašanje sustava na javno dostupnim skupovima slika. U završnom radu također se daje uvid u teme umjetnih neuronskih mreža, strojnog i dubokog učenja te konvolucijskih neuronskih mreža. Govori se o arhitekturi neuronskih mreža i o procesu učenja i testiranja istih, o algoritmima strojnog učenja te usporedbi strojnog s dubokim učenjem. Za ostvarenje sustava u programskom jeziku Python korišten je model konvolucijske neuronske mreže, te je stoga dan uvid u arhitekturu konvolucijskih neuronskih mreža. Naposljetku, dani su implementacija i rezultati sustava.
Abstract (english)
The task of this final thesis is to programmatically implement a system for traffic sign recognition in images captured from moving vehicles and examine the behavior of the system on publicly available image datasets. The thesis also provides insights into the topics of artificial neural networks, machine learning, deep learning, and convolutional neural networks. It discusses the architecture of neural networks and the process of training and testing them, as well as machine learning algorithms and a comparison between machine learning and deep learning. To implement the system in the Python programming language, a convolutional neural network model was used, and therefore an overview of convolutional neural network architecture is provided. Finally, the thesis presents the implementation and results of the system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:455537
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 on2023-10-11 08:52:56