prikaz prve stranice dokumenta Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja
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undergraduate thesis
Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:238576
Rastovski, Robert
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Rastovski, R. (2021). Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:238576

Rastovski, Robert. "Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:238576

Rastovski, Robert. "Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:238576

Rastovski, R. (2021). 'Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:238576

Rastovski R. Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:238576

R. Rastovski, "Predviđanje čovjekove trajektorije korištenjem metoda strojnog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:238576

Metadata
TitlePredviđanje čovjekove trajektorije korištenjem metoda strojnog učenja
Title (english)Human trajectory prediction using machine learning methods
AuthorRobert Rastovski
MentorIvan Marković (mentor)
Committee memberIvan Marković (predsjednik povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
Committee memberAnđela Jurić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-05, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Predviđanje trajektorije provedeno je korištenjem dva modela. Prvi model, model konstantne brzine, temelji se na nekoliko posljednjih položaja i srednjoj brzini bez algoritama strojnog učenja. Drugi model, model linearne regresije, temelji se na metodi strojnog učenja, a to je linearna regresija. Model linearne regresije koristi nekoliko položaja te računa brzinu koja minimizira grešku budućih položaja. Model se trenira korištenjem tih podataka te zatim koristi za predviđanje na neviđenim skupovima podataka. Rezultati oba modela su analizirani i uspoređeni.
Abstract (english)
Human trajectory prediction was implemented using two models. The first model, the constant velocity model, is based on the last few positions and average velocity without machine learning methods. The second model, the linear regression model, is based on the machine learning method and that method is linear regression. The linear regression model is using the last few positions and calculates velocity which minimizes the error of future positions. Model is trained using those data and then it is used for prediction on unseen data. Results of both models are analyzed and compared.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:238576
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 on2023-01-14 21:32:15