prikaz prve stranice dokumenta Procjena poze sportaša temeljeno na dubokom učenju
No public access
undergraduate thesis
Procjena poze sportaša temeljeno na dubokom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:438963
Spajić, Jure
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Spajić, J. (2024). Procjena poze sportaša temeljeno na dubokom učenju (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:438963

Spajić, Jure. "Procjena poze sportaša temeljeno na dubokom učenju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:438963

Spajić, Jure. "Procjena poze sportaša temeljeno na dubokom učenju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:438963

Spajić, J. (2024). 'Procjena poze sportaša temeljeno na dubokom učenju', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:438963

Spajić J. Procjena poze sportaša temeljeno na dubokom učenju [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:168:438963

J. Spajić, "Procjena poze sportaša temeljeno na dubokom učenju", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:438963

Metadata
TitleProcjena poze sportaša temeljeno na dubokom učenju
Title (english)Athletes Pose Estimation Based on Deep Learning
AuthorJure Spajić
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
Committee memberMarin Kačan (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema rada je procjena poze sportaša temeljeno na metodama dubokog učenja. Duboko učenje je podgrana strojnog učenja koja sustav obrađuje na način koji je sličan ljudskom mozgu. Kao prikladan model odabrane su konvolucijske neuronske mreže, koje su se pokazale izuzetno učinkovitima u analizi i klasifikaciji slika. Opisan je skup podataka Leeds Sport Pose koji je podijeljen na skup za učenje, validaciju i testiranje, kako bi se osiguralo pravilno treniranje modela i procjena njegove izvedbe. Model je treniran da prepoznaje pravilne i nepravilne stavove kod surfera. Na kraju su dani prijedlozi poboljšanja i nadogradnje modela.
Abstract (english)
The topic of this project is the assessment of athlete poses based on deep learning methods. Deep learning is a subfield of machine learning that processes data in a way similar to the human brain. Convolutional neural networks (CNNs) have been selected as the appropriate model, as they have proven to be extremely effective in image analysis and classification. The Leeds Sport Pose dataset is described, which is divided into training, validation, and testing sets to ensure proper model training and performance evaluation. The model was trained to recognize correct and incorrect stances in surfers. Finally, suggestions for model improvement and upgrades are provided.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:438963
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 conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2024-10-12 22:08:37