Jichen Zhong
Papers
1
Total Citations
12
H-Index
1
About
Jichen Zhong is a researcher at the forefront of applying artificial intelligence and computer vision to civil and structural engineering. His work focuses on automating the traditionally labor-intensive inspection of reinforcement steel (rebar) placement in concrete structures. Zhong’s major contribution lies in developing a novel, vision-based deep learning framework that integrates computational geometry to automatically detect and measure the spacing of rebar spacers on reinforcement skeletons. This innovation directly addresses a critical quality control challenge in construction, replacing manual checks with a faster, more accurate, and non-contact method. His most cited paper, "Automatic spacing inspection of rebar spacers on reinforcement skeletons using vision-based deep learning and computational geometry" (2023), has already garnered 12 citations, signaling its immediate relevance and impact in the field. By bridging the gap between advanced AI techniques and practical construction needs, Zhong is paving the way for smarter, safer, and more efficient infrastructure development.
Research Focus
Key Achievements
Top Papers
- 1