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undergraduate thesis
Sustav za raspoznavanje prometnih znakova
2019. urn:nbn:hr:168:978800
Macuka, Mihael
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Macuka, M. (2019). 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:168:978800

Macuka, Mihael. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:978800

Macuka, Mihael. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:978800

Macuka, M. (2019). 'Sustav za raspoznavanje prometnih znakova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:978800

Macuka M. Sustav za raspoznavanje prometnih znakova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2025 January 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:978800

M. Macuka, "Sustav za raspoznavanje prometnih znakova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:978800

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Metadata
TitleSustav za raspoznavanje prometnih znakova
Title (english)System for Traffic Sign Recognition
AuthorMihael Macuka
MentorZoran Kalafatić (mentor)
Committee memberZoran Kalafatić (predsjednik povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
Committee memberIvan Grubišić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu implementiran je sustav za raspoznavanje prometnih znakova. Iako postoje različiti načini rješavanja problema, odabran je način rješavanja pomoću neuronske mreže. Sustav je implementiran za klasifikaciju pet vrste znakova te klasificira sa zadovoljavajućom točnošću koja prelazi 90\%. Neuronska se mreža sastoji od nekoliko slojeva gdje je ulazni sloj veličine 256 neurona, a izlazni 6 što predstavlja broj mogućih kombinacija prilikom klasifikacije (pet klasa prometnih znakova i jedna klasa za negative).
Abstract (english)
In this thesis a traffic sign recognition system is implemented. A neural network is used for solving this problem, although other methods exist. The system can classify 5 different types of traffic signs with an accuracy of over 90\%. The neural network consists of several layers, where the input layer contains 256 neurons, and the output layer consists 6, which represents the number of possible classifications (5 classes of traffic signs and 1 class for negatives).
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:978800
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 on2020-01-07 19:55:09