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This paper presents a new version of Dropout called Split Dropout (sDropout) and rotational convolution techniques to improve CNNs' performance on image classification.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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Recursive interferometric representation
S. Mallat · 2010
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Tiled convolutional neural networks
J. Ngiam, Z. Chen, D. Chia, P. W. Koh, Q. V. Le, and A. Y. Ng · 2010
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Traffic sign recognition with multi-scale convolutional networks
P. Sermanet and Y. LeCun · 2011
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Adaptive deconvolutional networks for mid and high level feature learning
M. D. Zeiler, G. W. Taylor, and R. Fergus · 2011
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Improving neural networks by preventing co-adaptation of feature detectors
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Group invariant scattering
S. Mallat · 2012
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Deep learning of invariant features via simulated fixations in video
W. Zou, S. Zhu, K. Yu, and A. Y. Ng · 2012
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Adaptive dropout for training deep neural networks
J. Ba and B. Frey · 2013
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Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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Unsupervised feature learning by augmenting single images
A. Dosovitskiy, J. T. Springenberg, and T. Brox · 2013
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Some improvements on deep convolutional neural network based image classification
Fast dropout training
S. Wang and C. Manning · 2013
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2013
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Deep symmetry networks
R. Gens and P. M. Domingos · 2014
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One weird trick for parallelizing convolutional neural networks
A. Krizhevsky · 2014
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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al · 2014
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A. G. Howard · 2013
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Building high-level features using large scale unsupervised learning
Q. V. Le · 2013
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Rotation, scaling and deformation invariant scattering for texture discrimination
L. Sifre and S. Mallat · 2013
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Regularization of neural networks using dropconnect
L. Wan, M. Zeiler, S. Zhang, Y. L. Cun, and R. Fergus · 2013
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K. Simonyan and A. Zisserman · 2014
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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