Fujia Wei1,2,*, Liyin Shen1, Yuanming Xiang2, Xingjie Zhang2, Yu Tang2, Qian Tan2
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 619-637, 2022, DOI:10.32604/cmes.2022.019082
- 14 March 2022
Abstract Concrete exterior quality is one of the important metrics in evaluating construction project quality. Among the defects affecting concrete exterior quality, bughole is one of the most common imperfections, thus detecting concrete bughole accurately is significant for improving concrete exterior quality and consequently the quality of the whole project. This paper presents a deep learning-based method for detecting concrete surface bugholes in a more objective and automatic way. The bugholes are identified in concrete surface images by Mask R-CNN. An evaluation metric is developed to indicate the scale of concrete bughole. The proposed approach can More >
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