A Computational Method for Real-time Roof Defect Segmentation in Robotic Inspection
Published in Computer-Aided Civil and Infrastructure Engineering, 2025
This paper introduces RRD-SegNet, a deep learning-based computational method designed for real-time roof defect segmentation in robotic inspection systems. The method enables automated detection and segmentation of roof defects, improving the efficiency and accuracy of construction inspection tasks.
Recommended citation: Zhao, X. and Jebelli, H. (2025). “A computational method for real-time roof defect segmentation in robotic inspection.” Computer-Aided Civil and Infrastructure Engineering, 40(23), 3596-3623.
Recommended citation: Zhao, X. and Jebelli, H. (2025). "A computational method for real-time roof defect segmentation in robotic inspection." Computer-Aided Civil and Infrastructure Engineering, 40(23), 3596-3623.
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