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master's thesis
Sustav za detekciju čučnjeva
2023. urn:nbn:hr:190:980946
Duvnjak, Matej
University of Rijeka
Faculty of Engineering
Department of Computer Engineering

Cite this document

Duvnjak, M. (2023). Sustav za detekciju čučnjeva (Master's thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:980946

Duvnjak, Matej. "Sustav za detekciju čučnjeva." Master's thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:980946

Duvnjak, Matej. "Sustav za detekciju čučnjeva." Master's thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:980946

Duvnjak, M. (2023). 'Sustav za detekciju čučnjeva', Master's thesis, University of Rijeka, Faculty of Engineering, accessed 16 November 2024, https://urn.nsk.hr/urn:nbn:hr:190:980946

Duvnjak M. Sustav za detekciju čučnjeva [Master's thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2023 [cited 2024 November 16] Available at: https://urn.nsk.hr/urn:nbn:hr:190:980946

M. Duvnjak, "Sustav za detekciju čučnjeva", Master's thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:190:980946

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Metadata
TitleSustav za detekciju čučnjeva
AuthorMatej Duvnjak
MentorMladen Tomić (mentor)
Committee memberIvan Štajduhar (predsjednik povjerenstva)
Committee memberSandi Ljubić (član povjerenstva)
Committee memberMladen Tomić (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Computer Engineering)
Rijeka
Defense date and country2023-03-22, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema rada izrada je cjelovitog rješenja brojača čučnjeva na Raspberry Pi računalu pomoću postojećih TensorFlow i OpenCV knjižnica i MoveNet modela strojnog učenja. Detaljno su se opisali korišteni alati i knjižnice te objasnili dijelovi programskog koda koji pristupaju kameri i detektiraju čučanj.
Abstract (english)
The topic of this paper is the creation of a complete squat counter solution on a Raspberry Pi computer using the existing TensorFlow and OpenCV libraries and MoveNet machine learning models. The tools and libraries used were described in detail as well as parts of the program code that access the camera and detect squat.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:980946
Study programmeTitle: Computer Engineering
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
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-03-21 12:09:26