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undergraduate thesis
Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma
Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. urn:nbn:hr:179:032543
Mijoč, Marko
University of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
Department of Electronics and Computing

Institutional repository: Repository of the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture

Cite this document

Mijoč, M. (2022). Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma (Undergraduate thesis). Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:179:032543

Mijoč, Marko. "Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma." Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:032543

Mijoč, Marko. "Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma." Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:179:032543

Mijoč, M. (2022). 'Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma', Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, accessed 04 July 2024, https://urn.nsk.hr/urn:nbn:hr:179:032543

Mijoč M. Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma [Undergraduate thesis]. Split: University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture; 2022 [cited 2024 July 04] Available at: https://urn.nsk.hr/urn:nbn:hr:179:032543

M. Mijoč, "Detekcija brodova na videima splitske luke pomoću YOLOv4 algoritma", Undergraduate thesis, University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:179:032543

Metadata
TitleDetekcija brodova na videima splitske luke pomoću YOLOv4 algoritma
Title (english)Detection of ships on the videos of Split Harbor with the help of YOLOv4 algorithm
AuthorMarko Mijoč
MentorSven Gotovac (mentor)
GranterUniversity of Split
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture
(Department of Electronics and Computing)
Split
Defense date and country2022-09-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu opisana je problem detekcija objekata kao i moderni pristup rješavanju ovoga problema s posebnim naglaskom na YOLO algoritam. U početku rada općenito su opisani prepoznavanje i detekcija objekata te primjena detekcije objekata u praksi. Nakon ovoga opisani su moderni pristupi i tehnologije koje se koriste za detekciju objekata. Ovo poglavlje opisuje umjetne neuronske mreže, duboko učenje i konvolucijske neuronske mreže. U nastavku je opisano kako YOLO primjenjuje koncepte iz prethodnog poglavlja te detalji tog algoritma. Predzadnje poglavlje opsuje praktični dio ovoga rada tj. primjenu detekcije objekata korištenjem YOLOv4 algoritma. U zadnjem poglavlju predstavlja se zaključak ovoga rada.
Abstract (english)
This paper describes the problem of object detection as well as a modern approach to solving this problem with special emphasis on the YOLO algorithm. At the beginning of this paper there are general descriptions of object recognition and object detection as well as the use of object detection in practice. After this, modern approaches and technologies used for object detection are described. This chapter describes artificial neural networks, deep learning, and convolutional neural networks. Next chapter describes how YOLO applies the concepts from the previous chapter and also describes details of that algorithm. The penultimate chapter describes the practical part of this work, i.e., the application of object detection using the YOLOv4 algorithm. The last chapter presents the conclusion of this paper.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:179:032543
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
Access conditionsAccess restricted to authenticated users
Terms of useLicence In copyright icon
Created on2023-06-06 12:34:37