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Deep neural networks have been exhibiting splendid accuracies in many of visual pattern classification problems.
Backpropagation applied to handwritten zip code recognition
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Improving neural networks by preventing co-adaptation of feature detectors
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Partially occluded pedestrian classification using part-based classifiers and restricted boltzmann machine model
S. Aly, L. Hassan, A. Sagheer, and H. Murase · 2013
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Maxout networks
I. J. Goodfellow, D. Warde-Farley, M. Mirza, A. C. Courville, and Y. Bengio · 2013
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Regularization of neural networks using dropconnect
Network in network
M. Lin, Q. Chen, and S. Yan · 2014
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Pedestrian detection using augmented training data
J. Nilsson, P. Andersson, I.-H. Gu, and J. Fredriksson · 2014
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Transformation pursuit for image classification
M. Paulin, J. Revaud, Z. Harchaoui, F. Perronnin, and C. Schmid · 2014
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Improving deep neural networks with probabilistic maxout units
J. T. Springenberg and M. Riedmiller · 2014
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Going deeper with convolutions
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Classifying plankton with deep neural networks, 2015
S. Dieleman · 2015
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L. Wan, M. Zeiler, S. Zhang, Y. L. Cun, and R. Fergus · 2013
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Stochastic pooling for regularization of deep convolutional neural networks
M. D. Zeiler and R. Fergus · 2013
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C.-Y. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu · 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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Deep Image: Scaling up image recognition
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