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undergraduate thesis
Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:261663
Jurič, Katarina
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Jurič, K. (2022). Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:261663

Jurič, Katarina. "Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:261663

Jurič, Katarina. "Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:261663

Jurič, K. (2022). 'Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 22 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:261663

Jurič K. Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 November 22] Available at: https://urn.nsk.hr/urn:nbn:hr:168:261663

K. Jurič, "Detekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:261663

Metadata
TitleDetekcija objekata u stvarnom vremenu korištenjem dubokih neuronskih mreža
Title (english)Real-time object detection using deep neural networks
AuthorKatarina Jurič
MentorIvan Marković (mentor)
Committee memberIvan Marković (član povjerenstva)
Committee memberLuka Petrović (član povjerenstva)
Committee memberKarlo Koledić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-09-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Kroz rad je opisana povijest razvoja računalnog vida. Objašnjena je arhitektura te princip rada konvolucijskih neuronskih mreža. Za detekciju objekata u stvarnom vremenu korišten je YOLOv3 algoritam, a rad sarži njegov opis kao i usporedbu s dru- gom sličnom konvolucijskom mrežom Fast R-CNN. Napisan je izvršni file koji u Ro- botskom Operacijskom Sustavu pokreće web kameru i YOLO što rezultira detekcijom objekata. Provjeravala se ovisnost točnosti detekcije objekta o njegovoj udaljenosti od web kamere. Najvažniji zaključak je da detekcija ovisi o kontekstu i ostalim objektima u slici.
Abstract (english)
The thesis describes the history of computer vision development. The architecture and working principles of convolutional neural networks are explained. The YOLOv3 algorithm was used for object detection in real time and the paper summarizes its description as well as a comparison with another similar convolutional network - Fast R-CNN. An executable file has been written in which the Robot Operating System starts the web camera and YOLO. The dependence of object detection accuracy on its distance from the web camera was checked. The most important conclusion is that detection depends on the context and other objects in the image.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:261663
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 on2023-01-15 10:26:42