Prepoznavanje prometnih znakova pomoću strojnog učenja

undergraduate thesis

• Title (english): Traffic Signs Recognition using Machine Learning
• Author: Dominik Begić
• Mentor: Marina Bagić Babac (mentor)
• Committee member: Marina Bagić Babac (predsjednik povjerenstva)
• Committee member: Marko Horvat (član povjerenstva)
• Committee member: Tomislav Kos (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-09-14, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Otkrivanje i prepoznavanje prometnih znakova jedna su od popularnijih tema računalnog vida i obrade slika posljednjih godina jer imaju važnu ulogu u autonomnoj vožnji i sigurnosti prometa. Različite vrste prometnih znakova teško je prepoznati i klasificirati u lošijim uvjetima vožnje. U ovom radu potrebno je predstaviti metode za prepoznavanje i klasifikaciju temeljem algoritama strojnog učenja. Cilj je dizajnirati i implementirati sustav za prepoznavanje koji sa slike prepoznaje i klasificira... More različite vrste prometnih znakova. Less

Abstract (english)

Traffic sign detection and recognition are one of the most popular topics of computer vision and image processing in recent years, as they play an important role in autonomous driving and traffic safety. A great variety of traffic signs are hard to be detected or classified especially if they are spoiled or the driving environment is complicated. In this thesis, the state-of-the-art methods for developing such a recognizer based on machine learning algorithms, are elaborated and discussed.... More The aim is to design and implement a recognizer that is able to detect and classify different types of traffic signs from images. Less

• Keywords: računalni vid; klasifikacija; konvolucijska neuronska mreža; machine learning
• Keywords (english): computer vision; classification; convolutional neural network; machine learning
• Language: english
• URN:NBN: urn:nbn:hr:168:777927
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 20:04:18