Shenali Kariyawasam
Papers
2
Total Citations
22
H-Index
2
About
Shenali Kariyawasam is a researcher focused on the intersection of computer vision and embedded systems, with a primary emphasis on real-time traffic sign and traffic light detection. Her major contribution lies in addressing a critical challenge in autonomous driving and intelligent transportation: achieving high detection accuracy in complex, real-world scenarios while maintaining real-time performance on resource-constrained hardware. Her most-cited work, "Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systems" (2022), proposes a simple, deep learning-based end-to-end detection framework that directly tackles the trade-off between computational efficiency and accuracy. This work has garnered significant attention, accumulating over 22 citations, and highlights her ability to bridge the gap between advanced deep learning models and practical deployment on embedded platforms. By focusing on real-time performance without sacrificing robustness, Kariyawasam’s research is paving the way for safer and more efficient autonomous navigation systems, making her a notable emerging voice in the field of edge AI for intelligent vehicles.
Research Focus
Key Achievements
Top Papers
- 1
- 2