Damith Anhettigama
Papers
2
Total Citations
22
H-Index
2
About
Damith Anhettigama is a researcher focused on advancing computer vision for autonomous driving, with a particular emphasis on real-time perception systems. His major contributions lie in developing efficient deep learning frameworks for traffic sign and traffic light detection, specifically optimized for embedded systems with limited computational resources. His most cited work, "Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systems" (2022), has garnered 18 citations, highlighting its significance in addressing the critical challenge of balancing detection accuracy with real-time performance in complex driving scenarios. Anhettigama's research is notable for proposing a simple yet effective end-to-end detection framework that enables reliable object recognition on resource-constrained hardware, a key requirement for practical deployment in autonomous vehicles and advanced driver-assistance systems. His work bridges the gap between high-accuracy computer vision models and the stringent latency and power constraints of embedded platforms, making him a valuable contributor to the field of efficient AI for transportation. Anhettigama's ongoing efforts continue to push the boundaries of what is achievable in real-time visual perception on edge devices.
Research Focus
Key Achievements
Top Papers
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- 2