Chi Zhang
Papers
2
Total Citations
80
H-Index
2
About
Chi Zhang is an emerging researcher at the intersection of computer vision, deep learning, and construction automation. His work focuses on developing intelligent detection and robotic systems for real-world industrial applications, with a particular emphasis on improving the reliability and precision of automated processes in the construction domain. Zhang's most significant contribution to date is SDS-YOLO, an improved vibratory position detection algorithm built upon the YOLOv11 framework, published in 2024 and already amassing an impressive 74 citations — a remarkable achievement for a paper less than a year old, signaling strong community interest in his approach. This work demonstrates his ability to adapt and enhance state-of-the-art object detection architectures for specialized, domain-specific challenges. Complementing this, his research on continuous concrete vibration methods for robots integrates spatial feature recognition with machine vision, advancing the frontier of autonomous construction robotics. Together, these contributions reflect Zhang's broader mission: bridging cutting-edge AI techniques with practical engineering needs. His rapid citation growth suggests that his work is resonating strongly within both the computer vision and construction technology communities, positioning him as a promising young voice in intelligent automation research.
Research Focus
Key Achievements
Top Papers
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