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master's thesis
DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU
2022. urn:nbn:hr:200:262075
Vukadin, Domagoj
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Communications
Chair of Electronics and Microelectronics

Cite this document

Vukadin, D. (2022). DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:262075

Vukadin, Domagoj. "DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:200:262075

Vukadin, Domagoj. "DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2022. https://urn.nsk.hr/urn:nbn:hr:200:262075

Vukadin, D. (2022). 'DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:200:262075

Vukadin D. DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2022 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:200:262075

D. Vukadin, "DETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:200:262075

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Metadata
TitleDETEKTIRANJE ARTEFAKTA SMRZAVANJA SLIKE U VIDEO SIGNALU ZASNOVANO NA STROJNOM UČENJU
Title (english)MACHINE LEARNING BASED FREEZING ARTIFACTS DETECTION IN VIDEO SIGNAL
AuthorDomagoj Vukadin
MentorMarijan Herceg (mentor)
Committee memberMarijan Herceg (predsjednik povjerenstva)
Committee memberMario Vranješ (član povjerenstva)
Committee memberRatko Grbić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Communications)
(Chair of Electronics and Microelectronics)
Osijek
Defense date and country2022-09-25, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Telecommunications and Informatics
Abstract
U radu je opisana i prikazana manifestacija artefakta smrzavanja slike u video signalu. Opisan je temeljni princip detekcije artefakta smrzavanja bez pristupa referentnom sadržaju, problemi pri detekciji koje potrebno uzeti u obzir te ideja rješenja zasnovana na strojnom učenju. Dan je pregled postojećih baza video sekvenci koje sadrže artefakt smrzavanja i pregled postojećih algoritama. Predstavljena su tri vlastita rješenja za detekciju artefakta smrzavanja zasnovana na strojnom učenju. Rezultati postojećih algoritama za detekciju artefakta smrzavanja uspoređeni su s vlastitim rješenjima.
Abstract (english)
This master’s thesis describes and presents manifestation of freezing artefact. The basic principle of no-reference freezing artefact detection, detection problems that need to be considered and the idea of a solution based on machine learning are described. An overview of the existing databases with video sequences containing the freezing artifact is given, as well as an overview of the existing algorithms. Three proposed solutions for freezing artifact detection based on machine learning are presented. The results of two existing no-reference freezing detection algorithms are compared with our own solutions.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:262075
Study programmeTitle: UNIVERSITY STUDY AUTOMOBILE COMPUTER AND COMMUNICATION
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka automobilskog računarstva i komunikacija (magistar/magistra inženjer/inženjerka automobilskog računarstva i komunikacija)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-12-19 11:33:20