[1] [1] SPANHOL F A,OLIVERIA L S,PETITJEAN C,et al.A dataset for breast cancer histopathological image classification[J].IEEE Transactions on Biomedical Engineering,2016,63(7):1455-1462.

[2] [2] ARAUJO T,ARESTA G,CASTRO E,et al.Classification of breast cancer histology images using convolutional neural networks[J].PloS One,2017,12(6):e0177544.

[3] [3] ZHOU H Y,YU S,BIAN C,et al.Comparing to learn:Surpassing imageNet pretraining on radiographs by comparing image representations［C］//International Conference on Medical Image Computer Assisted Intervention,October 4-8,2020,Lima,Peru.Berlin:Springer-Verlag,2020:398-407.

[5] [5] KHAN S U,ISLAM N,JAN Z,et al.A novel deep learning based framework for the detection and classification of breast cancer using transfer learning[J].Pattern Recognition Letters,2019,125:1-6.

[6] [6] VU T H,MOUSAVI H S,MONGA V,et al.Histopathological image classification using discriminative feature-oriented dictionary learing[J].IEEE Transaction on Medical Imaging,2016,35(3):738-751.

[9] [9] LIU G,REDA F A,SHIH K J,et al.Image inpainting for irregular holes using partial convolutions［EB/OL］.(2018-12-15)［2021-9-29］.https://arxiv.org/pdf/1804.07723.pdf/．

[12] [12] IOFFE S，SZEGEDY C.Batch normalization:accelerating deep network training by reducing internal covariate shift［EB/OL］.(2015-02-11)［2021-10-26］.https://arxiv.org/abs/1502.03167.

[13] [13] WOO S,PARK J,LEE J.Convolutional block attention module［C］//Proceeding of the European Conference on Computer Vision,September 8-14,2018,Munich,Germany.Berlin:Springer,2018:3-19.

[14] [14] HE K,ZHANG X,REN S,SUN J.Deep residul learning for Image recognition［C］//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,June 26-July 1,2016,Las Vegas.America.New York:IEEE,2016:770-778.