Lubna Shahid
Papers
1
Total Citations
14
H-Index
1
About
Lubna Shahid is a researcher whose work lies at the intersection of computer vision, robotics, and automated inspection systems. Her most-cited paper, "A hybrid vision-based surface coverage measurement method for robotic inspection" (2018), has garnered 14 citations, reflecting its practical relevance in advancing robotic quality control. Shahid’s key contribution is the development of a hybrid methodology that integrates visual data processing with robotic movement, enabling precise, real-time measurement of surface coverage during inspection tasks. This work addresses critical challenges in industrial automation, such as ensuring thorough defect detection and reducing human error. By combining algorithmic vision techniques with robotic navigation, Shahid has provided a scalable solution for manufacturing and infrastructure monitoring. Her research is notable for its applied focus, bridging theoretical computer vision with tangible engineering outcomes. As a researcher, Shahid demonstrates a commitment to enhancing the efficiency and reliability of automated systems, making her work valuable for students and professionals in robotics, AI, and industrial engineering. Her findings continue to influence subsequent studies in vision-based inspection, underscoring her role in shaping modern quality assurance practices.
Research Focus
Key Achievements
Top Papers
- 1