Zeshan Kareem

University of Engineering and Technology Taxila

Papers

Total Citations

H-Index

About

Zeshan Kareem is a researcher at the intersection of computer vision, embedded systems, and robotics, with a focus on enabling intelligent visual perception in resource-constrained environments. His most cited work, "Embedded System Design for Visual Scene Classification" (2018, 9 citations), addresses the growing demand for low-cost, compact visual sensing devices by proposing a framework that integrates efficient classification algorithms into embedded platforms. This contribution is pivotal for real-time applications in autonomous robotics and smart surveillance, where power and computational limits are critical. Kareem’s research bridges the gap between high-level scene understanding and practical hardware implementation, advancing the deployment of AI in edge devices. While his citation count reflects a nascent but promising impact, his work is gaining traction in communities seeking scalable, energy-efficient vision solutions. By tackling the challenges of visual scene classification on embedded systems, Kareem is laying groundwork for more responsive and autonomous robotic systems, making his research a valuable resource for students and engineers exploring the future of intelligent, low-power perception.