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Analysis and classification tools for automatic process of punches and kicks recognition

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dc.title Analysis and classification tools for automatic process of punches and kicks recognition en
dc.contributor.author Lapková, Dora
dc.contributor.author Komínková Oplatková, Zuzana
dc.contributor.author Pluháček, Michal
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Adámek, Milan
dc.relation.ispartof Pattern Recognition and Classification in Time Series Data
dc.identifier.isbn 978-1-5225-0566-2
dc.identifier.isbn 1-5225-0565-2
dc.identifier.isbn 978-1-5225-0565-5
dc.date.issued 2016
dc.citation.spage 127
dc.citation.epage 151
dc.type bookPart
dc.language.iso en
dc.publisher IGI Global
dc.identifier.doi 10.4018/978-1-5225-0565-5.ch006
dc.relation.uri https://www.igi-global.com/chapter/analysis-and-classification-tools-for-automatic-process-of-punches-and-kicks-recognition/160623
dc.description.abstract This chapter deals with the pattern recognition in the time series. The data was obtained from the measurement of the force profiles via strain gauge sensor. This pattern recognition should help to classify different techniques of the professional defence (direct punch, direct and round kicks) and gender of the attacker. The aim is to find a suitable feature sets from the measured raw data which has to be transferred in appropriate way; in the case of this research spectral analysis or discrete cosine transformation were used. Based on the previous experience of authors, artificial neural networks with Levenberg-Marquardt training algorithm were selected as a classifier. In these experimentations, students from the Faculty of Applied Informatics, Tomas Bata University in Zlin participated. The results were successful and higher level than expected accuracy of 85% was achieved. The future plans include involving more participants and repeating the simulations to confirm the proposed technique. © 2017, by IGI Global. All rights reserved. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008023
utb.identifier.rivid RIV/70883521:28140/16:43875025!RIV17-GA0-28140___
utb.identifier.obdid 43875729
utb.identifier.scopus 2-s2.0-85013129689
utb.source c-scopus
dc.date.accessioned 2018-07-27T08:47:40Z
dc.date.available 2018-07-27T08:47:40Z
utb.contributor.internalauthor Lapková, Dora
utb.contributor.internalauthor Komínková Oplatková, Zuzana
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Adámek, Milan
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