[6] Long J, Shelhamer E, Darrell T, et al. Fully convolutional networks for semantic segmentation[C]//Computer Vision and Pattern Recognition, 2015: 3431-3440.
[7] Ronneberger O, Fischer P, Brox T, et al. U-Net: convolutional networks for biomedical image segmentation[C]//Medical Image Computing and Computer Assisted Intervention, 2015: 234-241.
[8] Liangchieh C, George P, Iasonas K, et al. Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018, 40(4): 834-848.
[9] Liangchieh C, George P, Schroff F, et al. Rethinkong Atrous convolution for semantic image segmentation[J]. 2017, arXiv: 1706, 05587.
[10] Liangchieh C, Yukun Zhu, George P, et al. Encoder-decoder with Atrous separable convolution for semantic image segmentation[C]//European Conference on Computer Vision, 2018: 801-818.
[11] HE Kai-ming, Z Xiang-yu, R Shao-qing. Deep residual learning for image recogniton[C]//Computer Vision and Pattern Recognition, 2015: 3431-3440.
[12] Ioffer S, Szegedy C. Batch normalization: accelerating deep network training by reducing internal covariate shift[C]//International Conference on Machine Learning, 2015.
