Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (1)
  • Open Access


    Deep Learning-Based Automatic Detection and Evaluation on Concrete Surface Bugholes

    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

    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 >

Displaying 1-10 on page 1 of 1. Per Page