The classification of taekwondo kicks via machine learning: A feature selection investigation

The classification of taekwondo kicks via machine learning: A feature selection investigation

Martial art strike classification by machine learning has drawn more attention over the past decade. The unique signal from each technique makes it harder to be recognized. Thus, this paper proposed an SVM, Random Forest, k-NN, and Naïve Bayes classification method applied to the time-domain signal...

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Bibliographic Details
Main Authors: Muhammad Syafi’i, Mass Duki, Muhammad Nur Aiman, Shapiee, Muhammad Amirul, Abdullah, Ismail, Mohd Khairuddin, Mohd Azraai, Mohd Razman, Anwar P. P., Abdul Majeed
Format: Article
Language:English
Published: Penerbit UMP 2021
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/33668/1/The%20classification%20of%20taekwondo%20kicks%20via%20machine%20learning.pdf

Internet

http://umpir.ump.edu.my/id/eprint/33668/1/The%20classification%20of%20taekwondo%20kicks%20via%20machine%20learning.pdf

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