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undergraduate thesis
Sustav za raspoznavanje prometnih znakova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:617388
Vitlov, Mihael
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Vitlov, M. (2020). 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:168:617388

Vitlov, Mihael. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:617388

Vitlov, Mihael. "Sustav za raspoznavanje prometnih znakova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:617388

Vitlov, M. (2020). 'Sustav za raspoznavanje prometnih znakova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 16 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:617388

Vitlov M. Sustav za raspoznavanje prometnih znakova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 July 16] Available at: https://urn.nsk.hr/urn:nbn:hr:168:617388

M. Vitlov, "Sustav za raspoznavanje prometnih znakova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:617388

Metadata
TitleSustav za raspoznavanje prometnih znakova
Title (english)System for Traffic Sign Recognition
AuthorMihael Vitlov
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 country2020-09-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U okviru završnog rada obrađeno je raspoznavanje prometnih znakova koristeći vlastitu konvolucijsku neuronsku mrežu, po arhitekturi sličnoj LeNet-5. Objašnjeni su pojmovi vezani uz umjetne neuronske mreže s fokusom na konvolucijske neuronske mreže. Za izgradnju mreže korištena je biblioteka PyTorch, a za treniranje i testiranje klasifikatora korišten je javno dostupan skup slika prometnih znakova GTSRB. Sustav se pokazao zadovoljavajućim s točnošću od 93%. Taj isti sustav je testiran i na skupu slika FER-MASTIF TS2009 na kojem je pokazao točnost od 71%.
Abstract (english)
The final paper deals with the recognition of traffic signs using convolutional neural network, according to an architecture similar to LeNet-5. Concepts related to artificial neural networks with a focus on convolutional neural networks are explained. The PyTorch library was used to build the network, and a publicly available set of GTSRB traffic sign images was used to train and test the classifier. The system proved to be satisfactory with an accuracy of 93%. This same system was also tested on the FER-MASTIF TS2009 image set, where it showed an accuracy of 71%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:617388
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 on2023-01-14 10:12:29