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master's thesis
Vrednovanje metoda za detekciju osoba u slikama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:182377
Marijan, Klara
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Marijan, K. (2022). Vrednovanje metoda za detekciju osoba u slikama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:182377

Marijan, Klara. "Vrednovanje metoda za detekciju osoba u slikama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:182377

Marijan, Klara. "Vrednovanje metoda za detekciju osoba u slikama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:182377

Marijan, K. (2022). 'Vrednovanje metoda za detekciju osoba u slikama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:182377

Marijan K. Vrednovanje metoda za detekciju osoba u slikama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:182377

K. Marijan, "Vrednovanje metoda za detekciju osoba u slikama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:182377

Metadata
TitleVrednovanje metoda za detekciju osoba u slikama
Title (english)Evaluation of methods for detection of persons in images
AuthorKlara Marijan
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberMarko Čupić (član povjerenstva)
Committee memberJan Šnajder (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu obrazložen je problem detekcije objekata te princip funkcioniranja jednoprolaznih i dvoprolaznih detektora. Objašnjene su razlike među njima te su detaljno opisane arhitekture modela YOLOv5 i Faster R-CNN kao predstavnika obje vrste detektora. Uhodano je učenje navedenih mreža na vlastitom skupu podataka s ciljem razvoja modela koji detektira ljude te razlikuje djecu od odraslih osoba. Napravljena je usporedba rezultata koje daju oba modela te su oni navedeni na kraju rada.
Abstract (english)
This paper explains the problem of object detection and the principle of functioning of single-shot and two-shot detectors. The differences between them are explained in the paper and the architectures of YOLOv5 and Faster R-CNN models are described in detail, as they are representatives of both types of detectors. These models are trained on a custom dataset with the aim of developing a model that detects people and distinguishes children from adults. A comparison of the results given by both models is made and they are listed at the end of the paper.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:182377
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 conditionsClosed access
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Created on2023-01-14 09:24:39