Raghav Khajuria
Papers
1
Total Citations
2
H-Index
1
About
Raghav Khajuria is a researcher at the forefront of edge computing and computer vision, specializing in optimizing person detection algorithms for resource-constrained devices. His most cited work, "Efficient Person Detection on Single Board Computers: A Comparative Analysis of Algorithms" (2024), provides a rigorous technical evaluation of detection methods tailored for single-board computers (SBCs). This study addresses the critical challenge of deploying AI on edge devices with limited computational power, offering a comparative framework that guides the selection of efficient algorithms for real-time applications. With 2 citations, this paper has already garnered attention for its practical insights into balancing accuracy and performance on platforms like Raspberry Pi and Jetson Nano. Khajuria’s contributions are pivotal for advancing edge AI, enabling smarter surveillance, autonomous systems, and IoT solutions without relying on cloud infrastructure. His work empowers developers and researchers to implement robust person detection in low-power environments, making him a key voice in the growing field of embedded vision.
Research Focus
Key Achievements
Top Papers
- 1