  This research proposes a Ground Penetrating Radar (GPR) data processing
method for non-destructive detection of tunnel lining internal defects, called
defect segmentation. To perform this critical step of automatic tunnel lining
detection, the method uses a CNN called Segnet combined with the Lov\'asz
softmax loss function to map the internal defect structure with GPR synthetic
data, which improves the accuracy, automation and efficiency of defects
detection. The novel method we present overcomes several difficulties of
traditional GPR data interpretation as demonstrated by an evaluation on both
synthetic and real datas -- to verify the method on real data, a test model
containing a known defect was designed and built and GPR data was obtained and
analyzed.
