Qishen Ha
Papers
1
Total Citations
177
H-Index
1
About
Qishen Ha is a leading researcher in autonomous vehicle perception, with a focus on multispectral object detection and sensor fusion. His most-cited work, "Multispectral Object Detection for Autonomous Vehicles" (2017, 177 citations), addresses a critical challenge in self-driving technology: robustly detecting cars, pedestrians, and bicycles under diverse environmental conditions. By integrating data from multiple spectral bands, Ha’s research enhances detection reliability in low-light, adverse weather, and complex traffic scenarios—key barriers to safe autonomous navigation. This foundational contribution has influenced subsequent advances in mobile robot automation, particularly in sensor fusion architectures for real-world deployment. Ha’s work bridges the gap between theoretical computer vision and practical autonomous driving systems, earning recognition for its impact on safety-critical perception. His research continues to shape the development of resilient object detection algorithms, making him a notable figure in the autonomous vehicle community.
Research Focus
Key Achievements
Top Papers
- 1Multispectral Object Detection for Autonomous Vehicles177 citations · 2017