Van-Viet Doan
Papers
1
Total Citations
5
H-Index
1
About
Dr. Van-Viet Doan is a leading researcher in computer vision, with a primary focus on real-time semantic image segmentation—a critical technology for enabling autonomous vehicles, robotics, and intelligent surveillance systems. His most-cited work, "Real-Time Image Semantic Segmentation Networks with Residual Depth-Wise Separable Blocks" (2018, 5 citations), introduces an innovative architectural design that balances accuracy and computational efficiency. By integrating residual connections with depth-wise separable convolutions, Dr. Doan’s network achieves high-quality pixel-level understanding of images while maintaining the speed necessary for real-time applications. This contribution addresses a fundamental challenge in deploying deep learning models on resource-constrained devices, bridging the gap between research and practical deployment. His work has been recognized for advancing the state-of-the-art in efficient semantic segmentation, directly impacting the development of safer autonomous navigation systems and more responsive visual perception technologies. Dr. Doan’s research continues to inspire new approaches in efficient deep learning architectures, making him a notable figure in the field of real-time computer vision.
Research Focus
Key Achievements
Top Papers
- 1