prikaz prve stranice dokumenta Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu
  Download
PDF 6.23 MB
master's thesis
Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu
Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2024. urn:nbn:hr:235:873965
Stepinac, Anamarija
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

Institutional repository: Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb

Cite this document

Stepinac, A. (2024). Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu (Master's thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:873965

Stepinac, Anamarija. "Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu." Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2024. https://urn.nsk.hr/urn:nbn:hr:235:873965

Stepinac, Anamarija. "Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu." Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2024. https://urn.nsk.hr/urn:nbn:hr:235:873965

Stepinac, A. (2024). 'Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu', Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 14 June 2024, https://urn.nsk.hr/urn:nbn:hr:235:873965

Stepinac A. Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2024 [cited 2024 June 14] Available at: https://urn.nsk.hr/urn:nbn:hr:235:873965

A. Stepinac, "Vizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu", Master's thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:235:873965

Metadata
TitleVizijski sustav za klasifikaciju objekata temeljen na YOLOv8 modelu
Title (english)A vision system for object classification based on the YOLOv8 model
AuthorAnamarija Stepinac
MentorTomislav Stipančić (mentor)
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2024-01-25, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mechanical Engineering
Abstract
Računalni vid je područje umjetne inteligencije, odnosno dubokog učenja, koje računalnim sustavima daje mogućnost vida. Za primjenu računalnog vida su razvijeni algoritmi za izvršavanje zadataka na slikama i videima, poput prepoznavanja objekata, klasifikacije i praćenja objekata. U radu je iznesena teorijska osnova potrebna za razumijevanje algoritama računalnog vida te je potkrijepljena primjerom u kojem je korišten algoritam YOLOv8. Algoritam je treniran i provjeren na označenom skupu podataka, a zatim testiran za prepoznavanje, klasifikaciju i praćenje na neviđenom primjeru.
Abstract (english)
Computer vision is an area of artificial intelligence, or rather deep learning, that gives computer systems the ability to see. Computer vision algorithms have been developed for performing tasks on images and videos, such as object recognition, classification and object tracking. The paper presents the theoretical basis necessary for understanding computer vision algorithms and is supported by an example in which the YOLOv8 algorithm was used. The algorithm was trained and validated on a labelled dataset and then tested for recognition, classification, and tracking on an unseen example.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:873965
Study programmeTitle: Mechanical Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka strojarstva (magistar/magistra inženjer/inženjerka strojarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-01-23 13:18:25