1 |
Ciregan, Dan, Ueli Meier, and Jürgen Schmidhuber, "Multi-column deep neural networks for image classification," Computer vision and pattern recognition (CVPR), 2012 IEEE conference on. IEEE, 2012. DOI: https://doi.org/10.1109/CVPR.2012.6248110
|
2 |
Parkhi, Omkar M., Andrea Vedaldi, and Andrew Zisserman, "Deep Face Recognition," BMVC, vol. 1. no. 3. 2015. DOI: https://doi.org/10.5244/C.29.41
|
3 |
Tian, Yonglong, et al, "Deep learning strong parts for pedestrian detection," Proceedings of the IEEE international conference on computer vision, 2015. DOI: https://doi.org/10.1109/ICCV.2015.221
|
4 |
Amodei, Dario, et al, "Deep speech 2: End-to-end speech recognition in english and mandarin," International Conference on Machine Learning. 2016.
|
5 |
Srivastava, Nitish, et al, "Dropout: a simple way to prevent neural networks from overfitting," Journal of Machine Learning Research 15.1 (2014): 1929-1958.
|
6 |
Wan, Li, et al, "Regularization of neural networks using dropconnect," Proceedings of the 30th international conference on machine learning (ICML-13). 2013.
|
7 |
Ioffe, Sergey, and Christian Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift," arXiv preprint arXiv:1502.03167 (2015).
|
8 |
Huang, Gao, et al, "Deep networks with stochastic depth," European Conference on Computer Vision. Springer, Cham, 2016. DOI: https://doi.org/10.1007/978-3-319-46493-0_39
|
9 |
Simonyan, Karen, and Andrew Zisserman, "Very deep convolutional networks for large-scale image recognition," arXiv preprint arXiv:1409.1556 (2014).
|
10 |
Iandola, Forrest, et al, "Densenet: Implementing efficient convnet descriptor pyramids," arXiv preprint arXiv:1404.1869 (2014).
|