[1] [1] WEI L,KANGSHUN L,YING H,et al.Defects of wheel hubs detection and recognition based on trend peak algorithm[J].Int.J.of Embedded Systems,2017,9(3):211.

[4] [4] YUE J, QIU Z and CHEN B. Application of wavelet transform to defect detection of wheelflats of railway wheels［C］//The 6th International Conference on Signal Processing,August 26-30,2002,Beijing,China.New York:IEEE, 2002:4.

[7] [7] STRECKER H.Scatter imaging of aluminum castings using an X-Ray fan beam and a pinhole camera[J].Material Evaluation,1982,40(9):1050-1056.

[8] [8] KEHOE A,PARKER G A.An intelligent knowledge based approach for the automated radiographic inspection of castings[J].NDT & E International,1992,25(1):23-36.

[9] [9] SERGIO H,DORIS S,DOMINGO M.Neuro-fuzzy method for automated defect detection in aluminium castings[J].Lecture Notes in Computer Science,2004,3212:826-833.

[10] [10] FERGUSON M, LEE Y T T, NARAYANAN A et al. A standardized PMML format for representing convolutional neural networks with application to defect detection[J].Smart and Sustainable Manufacturing Systems,2019, 3(1):79-97.

[12] [12] LI D W,XIE Q,GONG X X,et al.Automatic defect detection of metro tunnel surfaces using a vision-based inspection system[J].Advanced Engineering Informatics,2021,47:101206.

[15] [15] SAOOD A,HATEM I.COVID-19 lung CT image segmentation using deep learning methods:U-Net versus SegNet[J].BMC Medical Imaging,2021,21(1).

[16] [16] RONNEBERGER O, FISCHER P, BROX T. U-Net: convolutional networks for biomedical image segmentation［C］//International Conference on Medical Image Computing and Computer-Assisted Intervention,October 5-9, 2015,Munich,Germany.Berlin,Heidelberg:Springer-Verlag,2015:234-241.

[17] [17] ZHOU Z, SIDDIQUEE M M R, TAJBAKHSH N, et al. UNet++:a nested U-Net architecture for medical image segmentation［EB/OL］. (2018-07-18) ［2021-04-15］. https://arxiv.org/abs/1807.10165.

[19] [19] OKTAY O,SCHLEMPER J,FOLGOC L L,et al. Attention U-Net: learning where to look for the pancreas［EB/OL］. (2018-05-20) ［2021-04-15］. https://arxiv.org/abs/1804.03999v3.