Yanpeng Cao

Papers

Total Citations

301

H-Index

About

Yanpeng Cao is a leading researcher in computer vision and sensor fusion, with a focus on multispectral imaging and deep learning. His work bridges the gap between visible, thermal, and depth sensing, enabling robust perception in challenging environments. Cao’s most cited paper, “Pedestrian detection with unsupervised multispectral feature learning using deep neural networks” (145 citations), introduced a novel approach to fuse RGB and thermal data for improved detection in low-light conditions. He further advanced infrared imaging with “Cascaded Deep Networks With Multiple Receptive Fields for Infrared Image Super-Resolution” (103 citations), tackling the high cost and fabrication difficulty of high-resolution infrared detectors by proposing a cascaded deep network architecture. In “Depth and thermal sensor fusion to enhance 3D thermographic reconstruction” (53 citations), Cao developed a mobile, real-time method for creating 3D models with surface temperature data, with applications in medical imaging, energy auditing, and robotics. His contributions are widely recognized for enabling practical, low-cost solutions in night vision, surveillance, and intelligent systems, making him a key figure in the integration of thermal and depth sensing for real-world applications.