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izvor podataka: crosbi

Machine learning for data analysis in football: A survey of methods and problems (CROSBI ID 729261)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Tokić, Saša ; Panjkota, Ante ; Matetić, Maja Machine learning for data analysis in football: A survey of methods and problems // Annals of DAAAM for ... & proceedings of the ... International DAAAM Symposium ... / Katalinić, Branko (ur.). 2022. str. 0503-0510 doi: 10.2507/33rd.daaam.proceedings.070

Podaci o odgovornosti

Tokić, Saša ; Panjkota, Ante ; Matetić, Maja

engleski

Machine learning for data analysis in football: A survey of methods and problems

Machine learning is growing exponentially, and its applications are getting more and more traction in the sports analysis community in recent years. The application of machine learning methods on spatiotemporal data in sports like football is getting attention from football clubs, academics, and amateur analysts and is the main focus of this survey. This survey analyses and identifies current trends in research papers and literature to determine current and future applications in football analytics using spatiotemporal data.

spatiotemporal ; sports analytics, event data ; deep neural networks, machine learning

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Podaci o prilogu

0503-0510.

2022.

objavljeno

10.2507/33rd.daaam.proceedings.070

Podaci o matičnoj publikaciji

Katalinić, Branko

DAAAM International Vienna

978-3-902734-36-5

1726-9679

2304-1382

Podaci o skupu

33rd DAAAM International Symposium

predavanje

27.10.2022-28.10.2022

Beč, Austrija; online

Povezanost rada

Informacijske i komunikacijske znanosti, Računarstvo

Poveznice