Yiwen Bai
Papers
1
Total Citations
3
H-Index
1
About
Yiwen Bai is a researcher advancing the field of intelligent transportation systems through innovations in real-time semantic segmentation. Her primary research areas include computer vision, deep learning, and autonomous driving perception, with a focus on developing efficient neural network architectures for urban scene understanding. Bai’s most notable contribution is the Loss Compensation Fusion Network (LCFNet), introduced in her 2023 paper, which addresses the critical challenge of balancing high accuracy with fast processing in semantic segmentation of urban road scenes. This work is particularly valuable for applications like autonomous vehicles and traffic monitoring, where real-time performance is essential. With 3 citations to date, LCFNet has already garnered attention for its practical approach to improving segmentation quality without sacrificing speed. Bai’s research represents a meaningful step toward more reliable and responsive intelligent transportation systems, demonstrating her ability to tackle complex, real-world problems at the intersection of efficiency and precision.
Research Focus
Key Achievements
Top Papers
- 1