Liyue Lin
Papers
1
Total Citations
7
H-Index
1
About
Liyue Lin is a researcher at the forefront of action recognition and sports biomechanics, with a particular focus on table tennis motion analysis. Her work bridges computer vision and sports science, developing innovative deep learning approaches to capture and interpret complex athletic movements. In her most-cited study, "Table tennis motion recognition based on the bat trajectory using varying-length-input convolution neural networks" (2024), Lin introduced a novel method for recognizing table tennis strokes by analyzing bat trajectories with varying-length-input CNNs. This contribution addresses a critical challenge in sports technology—handling the temporal variability of human motion—and has immediate applications in biomechanical analysis, auxiliary training systems, virtual reality, and motion-sensing games. With 7 citations since publication, her work is gaining traction among researchers in smart homes, gaming, and security monitoring. Lin’s research not only advances the field of action recognition but also paves the way for practical tools that enhance athletic performance and immersive interactive experiences. Her interdisciplinary approach exemplifies how deep learning can transform our understanding of human movement.
Research Focus
Key Achievements
Top Papers
- 1