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crossrefApplied Sciences2025-05-12Cited by 7

Real-Time Accurate Determination of Table Tennis Ball and Evaluation of Player Stroke Effectiveness with Computer Vision-Based Deep Learning

Zilin He, Zeyi Yang, Jiarui Xu, Hongyu Chen, Xuanfeng Li, Anzhe Wang, Jiayi Yang, Gary Chi-Ching Chow, Xihan Chen

The adoption of artificial intelligence (AI) in sports training has the potential to revolutionize skill development, yet cost-effective solutions remain scarce, particularly in table tennis. To bridge this gap, we present an intelligent training system leveraging computer vision and machine learning for real-time performance analysis. The system integrates YOLOv5 for high-precision ball detection (98% accuracy) and MediaPipe for athlete posture evaluation. A dynamic time-wrapping algorithm further assesses stroke effectiveness, demonstrating statistically significant discrimination between beginner and intermediate players (p = 0.004 and Cohen’s d = 0.86) in a cohort of 50 participants. By automating feedback and reducing reliance on expert observation, this system offers a scalable tool for coaching, self-training, and sports analysis. Its modular design also allows adaptation to other racket sports, highlighting broader utility in athletic training and entertainment applications.

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An Accurate Deep Learning-Based Computer-Aided Diagnosis System for Gastrointestinal Disease Detection Using Wireless Capsule Endoscopy Image Analysis

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crossrefApplied Sciences2023-12-29Cited by 17

Real-Time Machine Learning for Human Activities Recognition Based on Wrist-Worn Wearable Devices

Alexandru Iulian Alexan, Anca Roxana Alexan, Stefan Oniga

Wearable technologies have slowly invaded our lives and can easily help with our day-to-day tasks. One area where wearable devices can shine is in human activity recognition, as they can gather sensor data in a non-intrusive way. We describe a real-time activity recognition syste…

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