Jihan Zhang
Papers
3
Total Citations
125
H-Index
2
About
Jihan Zhang is a leading researcher at the intersection of civil infrastructure inspection and autonomous robotic systems. Their work focuses on revolutionizing how we maintain critical infrastructure by integrating unmanned systems with advanced deep learning techniques. Zhang's most impactful contribution is a comprehensive review and algorithm comparison for crack classification, segmentation, and detection, which has garnered 88 citations and serves as a foundational resource for the field. They further advanced the domain by creating a high-resolution infrastructure defect detection dataset validated with deep learning, addressing the critical need for robust training data in automated visual inspection. This work, cited 35 times, demonstrates how unmanned robots can replace labor-intensive manual inspection with more efficient, comprehensive solutions. Zhang has also tackled the challenge of multi-robot coordination in unstructured environments, developing innovative sensor-based coverage control methods with spatial separation. Their research directly addresses the practical challenge of optimizing task efficiency in complex, obstacle-dense scenarios. Through these contributions, Zhang is helping to transform how we monitor and maintain our aging infrastructure, making inspection processes safer, faster, and more reliable through the power of robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
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