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...
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...
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...
International journal of sports physiology and performance
Feb 9, 2017
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...
OBJECTIVE: Early detection of knee osteoarthritis is crucial for improving patient outcomes. While conventional imaging methods often fail to detect early changes and require specialized expertise for interpretation, this study aimed to investigate t...
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