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master's thesis
Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:200483
Bakarić, Dominik
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bakarić, D. (2024). Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:200483

Bakarić, Dominik. "Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:200483

Bakarić, Dominik. "Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:200483

Bakarić, D. (2024). 'Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 March 2025, https://urn.nsk.hr/urn:nbn:hr:168:200483

Bakarić D. Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2025 March 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:200483

D. Bakarić, "Klasifikacija tipova vozila korištenjem dubokih neuronskih mreža", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:200483

Metadata
TitleKlasifikacija tipova vozila korištenjem dubokih neuronskih mreža
Title (english)Classification of vehicle types using deep neural networks
AuthorDominik Bakarić
MentorVedran Mornar (mentor)
Committee memberVedran Mornar (predsjednik povjerenstva)
Committee memberGordan Gledec (član povjerenstva)
Committee memberMarko Horvat (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-12, Croatia
Abstract
U današnje vrijeme, napretkom u području prepoznavanja objekata i računalnom vidu, jasno se vidi mogućnost primjene tih tehnologija u prometu i transportu. Te tehnologije mogu se primjenjivati na razne aspekte prometa kao što su regulacija prometa, sigurnost u prometu te razvoj autonomnih vozila. U sklopu ovog rada treba ostvariti model koji je će na slici prepoznavati vozila te ih klasificirati u kategorije kao što su automobil, motocikl, autobus, kamion ili kombi. Za realizaciju tog zadatka... More koristiti biblioteku Tensorflow 2 programskog jezika Python s ciljem izgradnje dubokog modela koji je baziran na konvolucijskim neuronskim mrežama te treniran korištenjem metoda prenesenog učenja. Less
Abstract (english)
Nowadays, with progress in the field of object recognition and computer vision, the possibility of applying these technologies in traffic and transport is clearly visible. These technologies can be applied to various aspects of traffic such as traffic regulation, traffic safety and the development of autonomous vehicles. As part of this work, a model should be created that will recognize vehicles in the image and classify them into categories such as car, motorcycle, bus, truck or van. To... More realize this task, we use the Tensorflow 2 library of the Python programming language with the aim of building a deep model based on convolutional neural networks and trained using transfer learning methods. Less
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:200483
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
Access conditionsOpen access
Terms of useLicence In copyright icon
Public note
Created on2024-10-12 20:00:50
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