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Track and Field

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Use of Machine Learning to Model Volume Load Effects on Changes in Jump Performance.

International journal of sports physiology and performance
PURPOSE: To use an artificial neural network (ANN) to model the effect of 15 weeks of resistance training on changes in countermovement jump (CMJ) performance in male track-and-field athletes.

The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...

Footwork recognition and trajectory tracking in track and field based on image processing.

Scientific reports
In track and field sports, footwork can greatly affect the effect and performance of sports. Accurate footwork can effectively improve the performance of professional athletes, and for ordinary trainers, it can reduce the probability of training inju...