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Tennis

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Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

International journal of sports physiology and performance
CONTEXT: Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not p...

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.

Journal of sports sciences
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...

Learning Three Dimensional Tennis Shots Using Graph Convolutional Networks.

Sensors (Basel, Switzerland)
Human movement analysis is very often applied to sport, which has seen great achievements in assessing an athlete's progress, giving further training tips and in movement recognition. In tennis, there are two basic shots: forehand and backhand, which...

Application of deep learning in automatic detection of technical and tactical indicators of table tennis.

PloS one
A DCNN-LSTM (Deep Convolutional Neural Network-Long Short Term Memory) model is proposed to recognize and track table tennis's real-time trajectory in complex environments, aiming to help the audiences understand competition details and provide a ref...