[1] Kong X Y, Wang R Z. Artificial intelligence and its application in medical field[J]. Journal of Medical Informatics, 37, 2-5(2016).

[2] Jin Z Y. Prospects and challenges: when medical imaging meets artificial intelligence[J]. Medical Journal of Peking Union Medical College Hospital, 9, 2-4(2018).

[3] Wu C Y, Yi B S, Zhang Y G et al. Retinal vessel image segmentation based on improved convolutional neural network[J]. Acta Optica Sinica, 38, 1111004(2018).

[4] Du J, Hu B L, Zhang Z F. Gastric carcinoma classification based on convolutional neural network and micro-hyperspectral imaging[J]. Acta Optica Sinica, 38, 0617001(2018).

[5] Chu J H, Li X C, Zhang J Q et al. Fine-granted segmentation method for three-dimensional brain tumors using cascaded convolutional network[J]. Laser & Optoelectronics Progress, 56, 101001(2019).

[6] Zhao P F, Zhao J J, Qiang Y et al. Study on detection method of pulmonary nodules with multiple input convolution neural network[J]. Computer Science, 45, 162-166(2018).

[7] Guan S, Zhang Q Y, Xie H W et al. Convolutional neural network model of CT images recognition[J]. Journal of Computer-Aided Design & Computer Graphics, 30, 1530-1535(2018).

[8] Yang F, Xie H W, Liu A Y. Lung nodule classification algorithm based on convolutional neural network[J]. Computer Engineering and Applications, 55, 145-150(2019).

[9] Miao G, Li C F. Detection of pulmonary nodules CT images combined with two-dimensional and three-dimensional convolution neural networks[J]. Laser & Optoelectronics Progress, 55, 051006(2018).

[10] Dai J F, Qi H Z, Xiong Y W et al. Deformable convolutional networks. [C]∥2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy. New York: IEEE, 764-773(2017).

[11] Deng Z P, Sun H, Lei L et al. Object detection in remote sensing imagery with multi-scale deformable convolutional networks[J]. Acta Geodaetica et Cartographica Sinica, 47, 1216-1227(2018).

[12] Tran D, Bourdev L, Fergus R et al. Learning spatiotemporal features with 3D convolutional networks. [C]∥2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile. New York: IEEE, 4489-4497(2015).

[13] Ji S W, Xu W, Yang M et al. 3D convolutional neural networks for human action recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 221-231(2013).

[14] Long J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 7-12, 2015, Boston, USA. New York: IEEE, 3431-3440(2015).

[15] Emre Yurdakul E, Yemez Y. Semantic segmentation of RGBD videos with recurrent fully convolutional neural networks. [C]∥Proceedings of the IEEE International Conference on Computer Vision, October 22-29, 2017, Venice, Italy. New York: IEEE, 367-374(2017).

[16] Hu Q, Qin L, Huang Q M. A survey on visual human action recognition[J]. Chinese Journal of Computers, 36, 2512-2524(2013).

[17] Zhu H L, Zhu C S, Xu Z G. Research advances on human activity recognition datasets[J]. Acta Automatica Sinica, 44, 978-1004(2018).