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undergraduate thesis
Detekcija pješaka dubokim neuronskim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:165389
Budimir, Lovre Antonio
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Budimir, L. A. (2018). Detekcija pješaka dubokim neuronskim mrežama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:165389

Budimir, Lovre Antonio. "Detekcija pješaka dubokim neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:165389

Budimir, Lovre Antonio. "Detekcija pješaka dubokim neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:165389

Budimir, L. A. (2018). 'Detekcija pješaka dubokim neuronskim mrežama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:165389

Budimir LA. Detekcija pješaka dubokim neuronskim mrežama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 November 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:165389

L. A. Budimir, "Detekcija pješaka dubokim neuronskim mrežama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:165389

Metadata
TitleDetekcija pješaka dubokim neuronskim mrežama
Title (english)Pedestrian Detection Using Deep Neural Networks
AuthorLovre Antonio Budimir
MentorSven Lončarić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberNikola Banić (član povjerenstva)
Committee memberIvana Zadro (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U posljednjih nekoliko godina napredni sustavi za pomoć u vožnji preuzimaju sve veću ulogu u sprječavanju prometnih nesreća uzrokovanih ljudskom nepažnjom. Jedna od glavnih funkcionalnosti takvih sustava je mogućnost detekcije pješaka. U sklopu ovog rada opisane su konvolucijske neuronske mreže i njihove glavne značajke. Proučene su poznate arhitekture konvolucijskih neuronskih mreža koje u posljednjih nekoliko godina postižu jako dobre rezultate u području klasifikacije i detekcije objekata na slikama. Na temelju proučenih arhitektura odabran je model koji je treniran i testiran na prikupljenoj bazi slika prometnih scena. Navedeni model zatim je implementiran u sustav za detekciju pješaka.
Abstract (english)
In recent years, advanced driving assistance systems have taken an increasingly significant role in preventing traffic accidents caused by human negligence. One of the main functionalities of such systems is the ability to detect pedestrians. This paper describes the convolutional neural networks and their key features. Known architectures of convolutional neural networks, which in recent years have achieved very good results in the field of classification and detection of objects in the images, have been researched. Based on the studied architecture, a model was selected, trained and tested on the collected image dataset of traffic scenarios. That model was used in an implementation of a pedestrian detection system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:165389
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 on2019-03-13 19:24:36