Yufeng Huang

Papers

Total Citations

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About

Yufeng Huang is a researcher specializing in computer vision and automated defect detection, with a particular focus on infrared imaging for power infrastructure diagnostics. Their most-cited work, "Infrared Image Defect Diagnosis through LAB Space Transformation" (2019), introduces an innovative approach that leverages LAB color space transformation to enhance thermal image analysis. This method enables automatic segmentation and template recognition of infrared photos captured by inspection robots, significantly reducing the need for manual human review in identifying equipment faults. By combining image processing techniques with robotic inspection systems, Huang's research offers a low-cost, scalable solution for predictive maintenance in the energy sector. Though early in their citation impact, with 2 citations to date, this work demonstrates practical promise in bridging computer vision and industrial automation. Huang's contributions are particularly valuable for researchers and engineers seeking to deploy autonomous diagnostic tools in real-world power grid monitoring, where timely defect detection can prevent costly failures and improve system reliability. Their work represents a meaningful step toward integrating intelligent image analysis into routine infrastructure maintenance workflows.