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Deep Convolutional Neural Networks (CNN) enforces supervised information only at the output layer, and hidden layers are trained by back propagating the prediction error from the output layer without explicit supervision.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. E. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. E. Hubbard, and L. D. Jackel · 1989
Earlier work this paper cites.
Gradient-based learning applied to document recognition
Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner · 1998
Earlier work this paper cites.
Greedy layer-wise training of deep networks
Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle · 2006
Earlier work this paper cites.
One-shot learning of object categories
F. Li, R. Fergus, and P. Perona · 2006
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and F. Li · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
Earlier work this paper cites.
Robust face recognition via sparse representation
J. Wright, A. Y. Yang, A. Ganesh, S. S. Sastry, and Y. Ma · 2009
Earlier work this paper cites.
Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
Earlier work this paper cites.
3d convolutional neural networks for human action recognition
S. Ji, W. Xu, M. Yang, and K. Yu · 2010
Earlier work this paper cites.
Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
Earlier work this paper cites.
Learning a discriminative dictionary for sparse coding via label consistent K-SVD
Z. Jiang, Z. Lin, and L. S. Davis · 2011
Earlier work this paper cites.
Sparse dictionary-based representation and recognition of action attributes
Q. Qiu, Z. Jiang, and R. Chellappa · 2011
Earlier work this paper cites.
Fisher discrimination dictionary learning for sparse representation
M. Yang, L. Zhang, X. Feng, and D. Zhang · 2011
Earlier work this paper cites.
Improving neural networks by preventing co-adaptation of feature detectors
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
UCF101: A dataset of 101 human actions classes from videos in the wild
K. Soomro, A. Roshan Zamir, and M. Shah · 2012
Cited alongside, same era.
Maxout networks
I. J. Goodfellow, D. Warde-Farley, M. Mirza, A. C. Courville, and Y. Bengio · 2013
Cited alongside, same era.
Regularization of neural networks using dropconnect
L. Wan, M. D. Zeiler, S. Zhang, Y. LeCun, and R. Fergus · 2013
Cited alongside, same era.
Action recognition with improved trajectories
H. Wang and C. Schmid · 2013
Cited alongside, same era.
Stochastic pooling for regularization of deep convolutional neural networks
M. D. Zeiler and R. Fergus · 2013
Cited alongside, same era.
Discriminative unsupervised feature learning with convolutional neural networks
A. Dosovitskiy, J. T. Springenberg, M. Riedmiller, and T. Bro · 2014
Cited alongside, same era.
Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. A. Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
Later among the works it cites.
THUMOS challenge: Action recognition with a large number of classes
A. Gorban, H. Idrees, Y.-G. Jiang, A. Roshan Zamir, I. Laptev, M. Shah, and R. Sukthankar · 2015
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Later among the works it cites.
Beyond gaussian pyramid: Multi-skip feature stacking for action recognition
Z. Lan, M. Lin, X. L. A. G. Hauptmann, and B. Raj · 2015
Later among the works it cites.
Deeply-supervised nets
C. Lee, S. Xie, P. W. Gallagher, Z. Zhang, and Z. Tu · 2015
Later among the works it cites.
Beyond short snippets: Deep networks for video classification
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. B. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Cited alongside, same era.
Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. B. Girshick, S. Guadarrama, and T. Darrell · 2014
Cited alongside, same era.
Large-scale video classification with convolutional neural networks
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and F. Li · 2014
Cited alongside, same era.
Network in network
M. Lin, Q. Chen, and S. Yan · 2014
Cited alongside, same era.
Two-stream convolutional networks for action recognition in videos
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
J. Y. Ng, M. J. Hausknecht, S. Vijayanarasimhan, O. Vinyals, R. Monga, and G. Toderici · 2015
Later among the works it cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
A. S. Razavian, J. Sullivan, A. Maki, and S. Carlsson · 2015
Later among the works it cites.
Deeply learned face representations are sparse, selective, and robust
Y. Sun, X. Wang, and X. Tang · 2015
Later among the works it cites.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
Later among the works it cites.
Action recognition with trajectory-pooled deep-convolutional descriptors
L. Wang, Y. Qiao, and X. Tang · 2015
Later among the works it cites.
Towards Good Practices for Very Deep Two-Stream ConvNets
L. Wang, Y. Xiong, Z. Wang, and Y. Qiao · 2015
Later among the works it cites.
A discriminative CNN video representation for event detection
Z. Xu, Y. Yang, and A. G. Hauptmann · 2015
Later among the works it cites.
Deep representation learning with target coding
S. Yang, P. Luo, C. C. Loy, K. W. Shum, and X. Tang · 2015
Later among the works it cites.
Evaluating two-stream CNN for video classification
H. Ye, Z. Wu, R. Zhao, X. Wang, Y. Jiang, and X. Xue · 2015
Later among the works it cites.
Exploiting image-trained CNN architectures for unconstrained video classification
S. Zha, F. Luisier, W. Andrews, N. Srivastava, and R. Salakhutdinov · 2015
Later among the works it cites.