Chul Hee Lee
Papers
1
Total Citations
10
H-Index
1
About
Chul Hee Lee is a researcher at the forefront of applying deep learning to structural engineering and construction automation. His work primarily focuses on computer vision and cross-modal data fusion for building infrastructure analysis. Lee’s most notable contribution is the development of an automatic curtain wall frame detection system, which integrates deep learning with cross-modal feature fusion to enhance the accuracy and efficiency of identifying structural components in complex building facades. This work, published in 2024, has already garnered 10 citations, signaling its immediate relevance to the field. By bridging the gap between artificial intelligence and construction engineering, Lee’s research addresses critical challenges in building inspection, maintenance, and retrofitting. His approach not only reduces manual labor but also improves safety and precision in structural assessments. Lee’s work is particularly impactful for students and researchers interested in the intersection of AI and civil infrastructure, offering a practical pathway toward smarter, more automated building management systems.
Research Focus
Key Achievements
Top Papers
- 1