Samreen Amir

Dawood University of Engineering and Technology

Papers

Total Citations

H-Index

About

Samreen Amir is a robotics researcher whose work focuses on autonomous navigation and vision-guided systems for agricultural and field robotics. Her most cited paper, "A Vision System for Autonomous Weed Detection Robot" (2010, 15 citations), presents a novel vision guidance system that employs image processing techniques and the Hough transform to detect inter-row crop spacing, enabling precise pose and orientation estimation for automated weed removal. This contribution addresses a critical challenge in precision agriculture—reducing herbicide use through targeted mechanical weeding. Her work on the "Kinect Controlled UGV" (2016, 4 citations) extends her expertise into human-robot interaction, using depth-sensing cameras for intuitive unmanned ground vehicle control. While her citation counts reflect a developing career, the foundational nature of her weed detection research has influenced subsequent work in agricultural robotics and computer vision for unstructured environments. Amir’s research bridges the gap between real-time visual perception and autonomous decision-making, offering practical solutions for sustainable farming and demonstrating the potential of low-cost sensors in field robotics.