Xinyan Xiang
Papers
1
Total Citations
7
H-Index
1
About
Xinyan Xiang is a researcher specializing in computer vision and embedded systems, with a particular focus on optimizing algorithms for real-time robotic applications. Their most cited work, "Research on Optimization of SURF Algorithm Based on Embedded CUDA Platform" (2018, 7 citations), addresses critical challenges in binocular stereo matching—a key technology for robot vision positioning. Xiang’s contributions target the practical limitations of existing algorithms, including poor portability, low real-time performance, and insufficient precision. By leveraging CUDA-accelerated embedded platforms, they developed optimizations that enhance computational efficiency without sacrificing accuracy, advancing the feasibility of vision-based robotic navigation in resource-constrained environments. This work bridges the gap between theoretical algorithm design and real-world deployment, offering scalable solutions for autonomous systems. Xiang’s research holds significance for students and engineers working on embedded vision, robotics, and GPU-accelerated computing, demonstrating how algorithmic refinement can unlock new capabilities in dynamic, real-time applications.
Research Focus
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Top Papers
- 1