Lingyun Xiao
Papers
1
Total Citations
104
H-Index
1
About
Lingyun Xiao is a leading researcher in the fields of computer vision and intelligent transportation systems, with a particular focus on deep learning applications for autonomous driving and traffic surveillance. His most influential work, "Real-time vehicle type classification with deep convolutional neural networks" (2017), has garnered over 104 citations, establishing a foundational approach for efficient, real-time vehicle recognition in complex urban environments. This contribution has been widely adopted in smart city infrastructure and traffic management systems, demonstrating significant practical impact. Xiao's research bridges the gap between theoretical deep learning advancements and real-world deployment, emphasizing both accuracy and computational efficiency. His work is frequently referenced in studies on vehicle detection, classification, and traffic flow analysis, making him a key figure in applied computer vision. For students and researchers exploring the intersection of AI and transportation, Lingyun Xiao's publications offer essential insights into scalable, real-time visual recognition systems that are shaping the future of intelligent mobility.
Research Focus
Key Achievements
Top Papers
- 1Real-time vehicle type classification with deep convolutional neural networks104 citations · 2017