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master's thesis
Duboki konvolucijski modeli za lokalizaciju objekata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:135574
Miko, Damjan
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Miko, D. (2018). Duboki konvolucijski modeli za lokalizaciju objekata (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:135574

Miko, Damjan. "Duboki konvolucijski modeli za lokalizaciju objekata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:135574

Miko, Damjan. "Duboki konvolucijski modeli za lokalizaciju objekata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:135574

Miko, D. (2018). 'Duboki konvolucijski modeli za lokalizaciju objekata', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 10 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:135574

Miko D. Duboki konvolucijski modeli za lokalizaciju objekata [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 August 10] Available at: https://urn.nsk.hr/urn:nbn:hr:168:135574

D. Miko, "Duboki konvolucijski modeli za lokalizaciju objekata", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:135574

Metadata
TitleDuboki konvolucijski modeli za lokalizaciju objekata
Title (english)Deep convolutional models for object localization
AuthorDamjan Miko
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberZoran Kalafatić (član povjerenstva)
Committee memberSlobodan Ribarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad bavi se metodama detekcije objekata konvolucijskim modelima. Detaljnije su proučeni i uspoređeni modeli SSD i YOLO te njihove novije verzije. Oni se baziraju na jednom unaprijednom prolazu kroz mrežu što ih čini brzim, a također daju i dobre rezultate. Napravljen je eksperiment koji koristi novije YOLO modele za lokalizaciju objekata na vlastitom skupu podataka. U tu svrhu koristi se snimka nogometne utakmice gdje su objekti za detekciju igrači oba tima i sudac. Modeli su evaluirani osnovnim mjerama i prikazani su njihovi rezultati detekcije.
Abstract (english)
This paper deals with the object detection method with convolutional models. There are studied and compared models like SSD, YOLO and their modern versions. They are based on only one forward pass through network what makes them fast and also give good results. An experiment is made which use newer YOLO models for localization objects on own dataset. For this purpose a tape of football game is use where object for detection are both teams and referee. Models are evaluated with basic measures and their detection results are shown.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:135574
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
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Created on2019-03-13 23:05:18