Deep Pyramidal Residual Networks with Separated Stochastic Depth

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2014

Earlier work this paper cites.

K. He, X. Zhang, S. Ren, and J. Sun, “Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,” CoRR, 2015. http://arxiv.org/abs/1502.01852

Original

2015

Earlier work this paper cites.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” Proc. CVPR, 2016

2016

Earlier work this paper cites.

G. Huang, Y. Sun, Z. Liu, D. Sedra, and K. Wein berger, “Deep networks with stochastic depth,” CoRR, 2016. https://arxiv.org/abs/1603.09382

Original

2016

Cited alongside, same era.

G. Huang, Z. Liu, and K.Q. Weinberger, “Densely connected convolutional networks,” CoRR, 2016. https://arxiv.org/abs/1608.06993

Original

2016

Cited alongside, same era.

D. Han, J. Kim, and J. Kim, ”Deep pyramidal residual networks,” CoRR, 2016. https://arxiv.org/abs/1610.02915

Original

2016

Closest in time.

S. Xie, R. Girshick, Z.T. Piotr Dollŕ, and K. He, “Aggregated residual transformations for deep neural networks,” CoRR, 2016. https://arxiv.org/abs/1611.05431

Original

2016

Closest in time.