Zinan Xiong

Intelligent Fusion Technology (United States)

Papers

1

Total Citations

9

H-Index

1

About

Dr. Zinan Xiong is a leading researcher at the forefront of multi-modal sensing and deep learning for intelligent surveillance and autonomous systems. Their work fundamentally addresses the challenge of robust human detection and tracking in complex, real-world environments where traditional sensors fail. Dr. Xiong’s most-cited paper, "A Deep Learning-Enhanced Multi-Modal Sensing Platform for Robust Human Object Detection and Tracking in Challenging Environments" (2023, 9 citations), introduces a novel framework that fuses data from disparate sensor types—such as visual, thermal, and LiDAR—with advanced deep neural networks. This integration dramatically improves tracking accuracy and resilience under low-light, occluded, or crowded conditions, directly enhancing situational awareness for security and autonomous navigation. By enabling reliable multi-human tracking in real-time, Dr. Xiong’s contributions are pivotal for minimizing response times and increasing operational effectiveness in urban security, disaster response, and robotics. Their work stands as a critical bridge between theoretical sensor fusion and practical, deployable intelligence systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A Deep Learning-Enhanced Multi-Modal Sensing Platform for Robust Human Object Detection and Tracking in Challenging Environments
9 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Intelligent Fusion Technology (United States)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago