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Convolutional Neural Networks have provided state-of-the-art results in several computer vision problems.
A theoretical framework for back-propagation
Y. LeCun, D. Touresky, G. Hinton, and T. Sejnowski · 1988
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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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Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Method of optimal directions for frame design
K. Engan, S. O. Aase, and J. Hakon Husoy · 1999
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Learning the parts of objects by nonnegative matrix factorization
D. D. Lee and H. S. Seung · 1999
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Learning methods for generic object recognition with invariance to pose and lighting
Y. LeCun, F. J. Huang, and L. Bottou · 2004
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Regularization and variable selection via the elastic net
H. Zou and T. Hastie · 2005
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A new method to assist small data set neural network learning
R. Mao, H. Zhu, L. Zhang, and A. Chen · 2006
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
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ImageNet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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What is the best multi-stage architecture for object recognition?
K. Jarrett, K. Kavukcuoglu, Y. LeCun, et al · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
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Face recognition for newborns: A preliminary study
S. Bharadwaj, H. S. Bhatt, R. Singh, M. Vatsa, and S. K. Singh · 2010
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Why does unsupervised pre-training help deep learning?
D. Erhan, Y. Bengio, A. Courville, P.-A. Manzagol, P. Vincent, and S. Bengio · 2010
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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Online learning for matrix factorization and sparse coding
J. Mairal, F. Bach, J. Ponce, and G. Sapiro · 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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Multiscale scattering for audio classification
J. Andén and S. Mallat · 2011
Cited alongside, same era.
One shot learning of simple visual concepts
B. Lake, R. Salakhutdinov, J. Gross, and J. Tenenbaum · 2011
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Dictionary learning
I. Tosic and P. Frossard · 2011
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Face recognition in unconstrained videos with matched background similarity
L. Wolf, T. Hassner, and I. Maoz · 2011
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Disguise detection and face recognition in visible and thermal spectrums
T. I. Dhamecha, A. Nigam, R. Singh, and M. Vatsa · 2013
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D. Mishkin and J. Matas · 2015
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Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
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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 · 2015
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Kernel principal component analysis network for image classification
D. Wu, J. Wu, R. Zeng, L. Jiang, L. Senhadji, and H. Shu · 2015
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A light CNN for deep face representation with noisy labels
X. Wu, R. He, Z. Sun, and T. Tan · 2015
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Regularization of neural networks using dropconnect
L. Wan, M. Zeiler, S. Zhang, Y. L. Cun, and R. Fergus · 2013
Cited alongside, same era.
MDLFace: Memorability augmented deep learning for video face recognition
G. Goswami, R. Bhardwaj, R. Singh, and M. Vatsa · 2014
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Cited alongside, same era.
PCANet: A simple deep learning baseline for image classification?
T.-H. Chan, K. Jia, S. Gao, J. Lu, Z. Zeng, and Y. Ma · 2015
Cited alongside, same era.
Reducing overfitting in deep networks by decorrelating representations
M. Cogswell, F. Ahmed, R. Girshick, L. Zitnick, and D. Batra · 2015
Cited alongside, same era.
Tensor object classification via multilinear discriminant analysis network
R. Zeng, J. Wu, L. Senhadji, and H. Shu · 2015
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Domain specific learning for newborn face recognition
S. Bharadwaj, H. S. Bhatt, M. Vatsa, and R. Singh · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Meta-learning with memory-augmented neural networks
A. Santoro, S. Bartunov, M. Botvinick, D. Wierstra, and T. Lillicrap · 2016
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Deep dictionary learning
S. Tariyal, A. Majumdar, R. Singh, and M. Vatsa · 2016
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Matching networks for one shot learning
O. Vinyals, C. Blundell, T. Lillicrap, D. Wierstra, et al · 2016
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Regularizing deep convolutional neural networks with a structured decorrelation constraint
W. Xiong, B. Du, L. Zhang, R. Hu, and D. Tao · 2016
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Low-shot visual recognition by shrinking and hallucinating features
B. Hariharan and R. Girshick · 2017
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Densely connected convolutional networks
G. Huang, Z. Liu, L. van der Maaten, and K. Q. Weinberger · 2017
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Face sketch matching via coupled deep transform learning
S. Nagpal, M. Singh, R. Singh, M. Vatsa, A. Noore, and A. Majumdar · 2017
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Scaling the scattering transform: Deep hybrid networks
E. Oyallon, E. Belilovsky, and S. Zagoruyko · 2017
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