Jianjun Tang
Papers
1
Total Citations
4
H-Index
1
About
Jianjun Tang is a researcher whose work sits at the intersection of sports science, machine vision, and intelligent motion analysis. His primary research focuses on applying computer vision and machine learning techniques to enhance athletic performance and injury prevention, with a particular emphasis on badminton. Tang’s most notable contribution is his 2021 paper, “Motion Capture and Intelligent Correction Method of Badminton Movement Based on Machine Vision,” which has garnered 4 citations. This work addresses a critical gap in amateur sports: the lack of proper medical supervision and health guidance. By developing a system that captures and corrects badminton movements in real time, Tang offers a scalable, technology-driven solution to reduce injury risk and improve technique among recreational players. His research bridges the gap between advanced computational methods and practical sports applications, making high-level training insights accessible to non-professionals. Though early in its citation impact, Tang’s work is foundational for the growing field of intelligent sports coaching systems, and it underscores his commitment to democratizing health and performance optimization through innovation.
Research Focus
Key Achievements
Top Papers
- 1