Yong Liang
Papers
1
Total Citations
3
H-Index
1
About
Dr. Yong Liang is a pioneering researcher at the forefront of computer vision and edge computing, with a primary focus on real-time stereo vision hardware acceleration. His most impactful work centers on developing efficient, low-power hardware architectures that enable embodied intelligence on edge platforms. In his landmark 2024 paper, "Real-Time Stereo Vision Hardware Accelerator: Fusion of SAD and Adaptive Census Algorithm," Dr. Liang introduced a novel fusion approach that balances the complementary strengths of Sum of Absolute Differences (SAD) and adaptive Census transforms. This innovation directly addresses the critical challenge of achieving high-accuracy depth perception while maintaining real-time performance and minimal power consumption—a bottleneck for applications in autonomous driving, robot navigation, and 3D reconstruction. Though his work is recent, its 3 citations already signal growing recognition in the field. Dr. Liang’s contributions are particularly notable for bridging the gap between algorithmic precision and hardware feasibility, offering a practical pathway toward deploying sophisticated stereo vision systems on resource-constrained edge devices. His research stands as a vital step toward truly autonomous machines that can perceive and interact with their environment in real time.
Research Focus
Key Achievements
Top Papers
- 1