Training a group of badminton serving machines to reproduce a rally

This paper proposes to train a group of badminton serving machines by a simple deep neural network (DNN) consisting of 8 dense layers. Our ultimate goal is to have the proposed system reproduce a badminton rally captured from social media such as YouTube. All the parameters of these serving machines need to be predicted from a trajectory image in a race video through a deep learning regression model. We can successfully estimate 10 trajectory parameters with an average RMSE loss of 0.087. I. Introduction II. System Model III. Reproducing One Shot by Regression IV. Experimental Results V. Conclusions
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Bibliographic Details
Subjects:
Notations:technical and natural sciences sport games
Tagging:künstliche Intelligenz deep learning maschinelles Lernen neuronale Netze
Published in:International Conference on Pervasive Artificial Intelligence (ICPAI), Taipei, Taiwan, 2020
Language:English
Published: 2020
Online Access:https://ieeexplore.ieee.org/document/9302654
Document types:congress proceedings
Level:advanced