Mohamed Sbihi
Papers
1
Total Citations
3
H-Index
1
About
Mohamed Sbihi is a researcher specializing in embedded systems, computer vision, and high-level synthesis for real-time applications. His work focuses on the efficient implementation of computationally intensive algorithms on low-cost parallel platforms, bridging the gap between software flexibility and hardware performance. Sbihi’s most notable contribution is his 2021 paper on the high-level synthesis implementation of monocular SLAM (Simultaneous Localization and Mapping), a critical technology for autonomous navigation in robotics and augmented reality. This work demonstrates how complex visual odometry tasks can be accelerated on resource-constrained devices, achieving real-time performance without sacrificing accuracy. While his citation count is still growing, the practical significance of his research is evident in its potential to democratize SLAM capabilities for embedded systems. Sbihi’s approach leverages modern FPGA and GPU architectures, offering a scalable pathway for deploying advanced computer vision in low-power environments. His contributions are particularly relevant for researchers and engineers seeking to integrate autonomous perception into cost-sensitive applications, from drones to mobile robots.
Research Focus
Key Achievements
Top Papers
- 1