Papers
1
Total Citations
6
H-Index
1
About
Jianzhen Li is a researcher at the forefront of computer vision and intelligent perception, with a primary focus on advancing deep learning techniques for structural health monitoring and building information modeling. His most-cited work, "An edge information fusion perception network for curtain wall frames segmentation" (2024, 6 citations), introduces a novel neural architecture that integrates edge-aware features with semantic segmentation to precisely identify and delineate curtain wall frames from complex urban imagery. This contribution addresses a critical challenge in automated building inspection and smart city infrastructure management, where accurate segmentation of glass facades and metal frameworks is essential for safety assessments and digital twin creation. Li’s approach leverages multi-scale feature fusion and attention mechanisms to enhance boundary detection, significantly improving segmentation accuracy in cluttered environments. Though early in its citation trajectory, this work has already garnered attention for its practical applicability in construction automation and structural integrity analysis. Li’s research bridges the gap between theoretical computer vision and real-world engineering needs, offering scalable solutions for urban asset management. His ongoing work promises to further integrate edge computing and real-time perception systems, positioning him as an emerging voice in applied AI for civil infrastructure.
Research Focus
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Top Papers
- 1