Ping-Han Chen
Papers
1
Total Citations
20
H-Index
1
About
Ping-Han Chen is a computer vision researcher whose work focuses on thermal imaging and intelligent surveillance systems. His most cited paper, "Thermal-Based Pedestrian Detection Using Faster R-CNN and Region Decomposition Branch" (2019, 20 citations), introduces an innovative method for detecting pedestrians in infrared thermal images, specifically designed for nighttime surveillance applications. This work addresses a critical challenge in computer vision—reliable pedestrian detection in low-light conditions—by combining the Faster R-CNN architecture with a region decomposition branch to improve accuracy. Chen's research bridges the gap between deep learning and real-world automation needs, with direct applications in video surveillance, autonomous robotics, and automotive safety systems. His contributions are particularly valuable for enhancing nighttime security and autonomous vehicle perception, where traditional visible-light cameras often fail. By advancing thermal-based detection methods, Chen is helping to make intelligent surveillance systems more robust and reliable across diverse lighting conditions, demonstrating the practical impact of his work in both academic and industrial contexts.
Research Focus
Key Achievements
Top Papers
- 1