Li-Sheng Hsu

National Yang Ming Chiao Tung University

Papers

1

Total Citations

19

H-Index

1

About

Li-Sheng Hsu is a leading researcher in visible light positioning (VLP) and optical wireless communication systems. His primary contributions lie in developing high-precision three-dimensional indoor positioning technologies that overcome fundamental physical limitations of light-based systems. In his landmark 2022 work, Hsu introduced the Two-Stage Neural Network (TSNN) combined with Received Intensity Selective Enhancement (RISE), achieving the first-ever demonstration of a 3D visible light-based indoor positioning system capable of mitigating light non-overlap zones—a critical challenge that previously degraded accuracy in real-world environments. This innovative approach has garnered 19 citations and established a new paradigm for robust indoor navigation. Hsu’s research bridges deep learning and optical engineering, enabling centimeter-level positioning accuracy for applications in autonomous robot navigation, asset tracking, and augmented reality. His work is particularly notable for addressing practical deployment issues, making VLP systems viable for large-scale implementation. By integrating neural network architectures with selective signal enhancement, Hsu continues to push the boundaries of what is achievable in visible light positioning, earning recognition as a pioneer in next-generation indoor localization technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
3D Visible Light-Based Indoor Positioning System Using Two-Stage Neural Network (TSNN) and Received Intensity Selective Enhancement (RISE) to Alleviate Light Non-Overlap Zones
19 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: National Yang Ming Chiao Tung University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago