The Classification of Skateboarding Tricks by Means of Support Vector Machine: An Evaluation of Significant Time-Domain Features-Reference-Cited by-同舟云学术

The Classification of Skateboarding Tricks by Means of Support Vector Machine: An Evaluation of Significant Time-Domain Features

Published:2020 Issue: Volume: Page:125-132
ISSN:1876-1100
Container-title:Embracing Industry 4.0
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Author:

Abdullah Muhammad Amirul^ORCID,Ibrahim Muhammad Ar Rahim,Shapiee Muhammad Nur Aiman,Abdul Majeed Anwar P. P.^ORCID,Mohd Razman Mohd Azraai,Musa Rabiu Muazu,Zakaria Muhammad Aizzat

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-6025-5_12

Reference12 articles.

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3. Büthe L, Blanke U, Capkevics H, Tröster G (2016) A wearable sensing system for timing analysis in tennis. In: 2016 IEEE 13th international conference on wearable and implantable body sensor networks (BSN). IEEE, pp 43–48

4. Connaghan D, Kelly P, O’Connor NE, Gaffney M, Walsh M, O’Mathuna C (2011) Multi-sensor classification of tennis strokes. In: SENSORS, 2011 IEEE. IEEE, pp 1437–1440

5. Adelsberger R, Tröster G (2013) Experts lift differently: classification of weight-lifting athletes. In: 2013 IEEE international conference on body sensor networks. IEEE, pp 1–6

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