prikaz prve stranice dokumenta Prepoznavanje objekata primjenom dubokog učenja
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undergraduate thesis
Prepoznavanje objekata primjenom dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:212650
Baće, Tara
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Baće, T. (2024). Prepoznavanje objekata primjenom dubokog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:212650

Baće, Tara. "Prepoznavanje objekata primjenom dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:212650

Baće, Tara. "Prepoznavanje objekata primjenom dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:212650

Baće, T. (2024). 'Prepoznavanje objekata primjenom dubokog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:212650

Baće T. Prepoznavanje objekata primjenom dubokog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 November 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:212650

T. Baće, "Prepoznavanje objekata primjenom dubokog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:212650

Metadata
TitlePrepoznavanje objekata primjenom dubokog učenja
Title (english)Object Detection Using Machine Learning
AuthorTara Baće
MentorGoran Delač (mentor)
Committee memberGoran Delač (predsjednik povjerenstva)
Committee memberMarin Kačan (član povjerenstva)
Committee memberIvan Grubišić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-06-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom istraživanju objašnjen je problem detekcije objekata u slikama te princip rada jednoprolaznih detektora. Proveden je trening modela YOLOv5 na vlastitom skupu podataka s ciljem razlikovanja glazbenih instrumenata. Uspoređeni su rezultati dobiveni nad različitim ulaznim skupovima podataka te je detaljno opisan postupak vrednovanja tih rezultata.
Abstract (english)
This research explains the problem of object detection in images and the working principle of single-shot detectors. The YOLOv5 model was trained on a custom dataset to distinguish musical instruments. The results obtained from different input datasets were compared, and the evaluation process of these results was described in detail.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:212650
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 on2024-10-12 20:00:35