Saurabh Chatterjee
Papers
1
Total Citations
4
H-Index
1
About
Saurabh Chatterjee is a researcher whose work lies at the intersection of computer vision, robotics, and automated inspection systems. His primary research focuses on developing algorithms for viewpoint planning and 3D image stitching, particularly for the inspection of large-scale industrial panels. His most-cited paper, "Viewpoint planning and 3D image stitching algorithms for inspection of panels" (2023), has garnered 4 citations, reflecting its relevance in optimizing robotic sensor placement and image reconstruction for quality control. Chatterjee’s contributions address critical challenges in automating visual inspection, enabling more efficient and accurate detection of defects in manufacturing environments. By integrating geometric reasoning with imaging techniques, his work advances the practical deployment of autonomous inspection systems. While his citation count is modest, it underscores a growing interest in his methodologies among peers in robotics and computer vision. Chatterjee’s research holds promise for reducing human error and increasing throughput in industrial settings, making him a notable emerging voice in the field of automated inspection and 3D reconstruction.
Research Focus
Key Achievements
Top Papers
- 1