Brijesh Jadav
Papers
1
Total Citations
5
H-Index
1
About
Brijesh Jadav is a computer vision and embedded systems researcher whose work focuses on enabling efficient, high-performance computer vision on heterogeneous multi-core architectures. His key research areas include heterogeneous computing, OpenVX framework implementation, and real-time vision processing for automotive, robotics, AR/VR, and industrial machine vision applications. His most notable contribution is a novel OpenVX implementation designed for heterogeneous multi-core systems integrating CPUs, GPUs, hardware accelerators (HWA), and DSPs. This work addresses the critical challenge of maximizing utilization across diverse computing elements while maintaining low latency—a fundamental requirement for modern embedded vision platforms. With 5 citations, this foundational paper has informed subsequent research into software frameworks that realize high utilization of heterogeneous computing elements. Jadav’s work is particularly significant for students and researchers exploring the intersection of computer vision and embedded systems, as it provides a practical blueprint for building efficient, scalable vision pipelines on increasingly complex hardware platforms.
Research Focus
Key Achievements
Top Papers
- 1Novel OpenVX implementation for heterogeneous multi-core systems5 citations · 2017