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) …