Xin-Yang Zeng

Papers

Total Citations

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About

Xin-Yang Zeng is a researcher specializing in computer vision and robotics for industrial safety inspection, with a particular focus on automated gauge detection and monitoring in high-voltage environments. His most-cited work, "Automatic Gauge Detection via Geometric Fitting for Safety Inspection" (2019, 16 citations), addresses a critical challenge in electrical substations: enabling inspection robots to autonomously analyze instrument readings in hazardous settings. By developing geometric fitting algorithms for gauge detection, Zeng's research reduces the need for skilled technicians to enter dangerous high-voltage areas, enhancing both safety and operational efficiency. His contributions bridge the gap between robotic perception and real-world industrial applications, offering practical solutions for infrastructure monitoring. Though his citation count reflects a focused, emerging career, Zeng's work is notable for its direct impact on safety protocols in power systems. His research demonstrates how computer vision techniques can be tailored to solve domain-specific problems, making him a promising figure in the intersection of robotics, safety engineering, and automated inspection systems.