[1] | ImageNet classification with deep convolutional neural networks. Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton, NIPS 2012. |
[2] | Visualizing and understanding convolutional networks. Zeiler, Matthew D., and Rob Fergus, ECCV 2014. |
[3] | Network in network. Lin, Min, Qiang Chen, and Shuicheng Yan, ICLR 2013. |
[4] | Going deeper with convolutions. Szegedy, Christian, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich, CVPR 2015. |
[5] | Very deep convolutional networks for large-scale image recognition. Simonyan, Karen, and Andrew Zisserman, ICLR 2015. |
[6] | Deep residual learning for image recognition. He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, CVPR 2016. |
[7] | Xception: Deep learning with depthwise separable convolutions. Chollet, François, CVPR 2017. |
[8] | Dynamic routing between capsules. Sabour, Sara, Nicholas Frosst, and Geoffrey E. Hinton, NIPS 2017. |
[9] | DARTs: Differentiable architecture search. Liu, Hanxiao, Karen Simonyan, and Yiming Yang, ICLR 2019. |
[10] | Dropout: a simple way to prevent neural networks from overfitting. Srivastava, Nitish, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov, The Journal of Machine Learning Research, 2014. |
[11] | Batch normalization: Accelerating deep network training by reducing internal covariate shift. Ioffe, Sergey, and Christian Szegedy, ICML 2015. |
[12] | Group normalization. Wu, Yuxin, and Kaiming He, ECCV 2018. |
[13] | Generative adversarial nets. Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio, NIPS 2014. |
[14] | You only look once: Unified, real-time object detection. Redmon, Joseph, Santosh Divvala, Ross Girshick, and Ali Farhadi, CVPR 2016. |
[15] | Mask R-CNN. He, Kaiming, Georgia Gkioxari, Piotr Dollár, and Ross Girshick, ICCV 2017. |
[16] | Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. MIT Press, 2016. |
[17] | Imagenet: A large-scale hierarchical image database. Deng, Jia, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei, CVPR 2009. [link] |
[18] | Microsoft coco: Common objects in context. Lin, Tsung-Yi, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick, ECCV 2014. [link] |
[19] | MorphNet: Fast & simple resource-constrained structure learning of deep networks. Gordon, Ariel, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, and Edward Choi, CVPR 2018. |