Deep learning based image recognition for crack and leakage defects of metro shield tunnel
The performance of traditional visual inspection by handcrafted features for crack and
leakage defects of metro shield tunnel is hardly satisfactory nowadays because it is low-
efficient to distinguish defects from some interference such as segmental joints, bolt holes,
cables and manual marks. Based on deep learning (DL), this paper proposes a novel image
recognition algorithm for semantic segmentation of crack and leakage defects of metro
shield tunnel using hierarchies of features extracted by fully convolutional network (FCN) …
leakage defects of metro shield tunnel is hardly satisfactory nowadays because it is low-
efficient to distinguish defects from some interference such as segmental joints, bolt holes,
cables and manual marks. Based on deep learning (DL), this paper proposes a novel image
recognition algorithm for semantic segmentation of crack and leakage defects of metro
shield tunnel using hierarchies of features extracted by fully convolutional network (FCN) …