Stacked Convolutional Auto-Encoders for Hierarchical Feature Extraction
暂无分享,去创建一个
Jürgen Schmidhuber | Jonathan Masci | Ueli Meier | Dan C. Ciresan | J. Schmidhuber | D. Ciresan | Jonathan Masci | U. Meier
[1] Mohammad Norouzi,et al. Stacks of convolutional Restricted Boltzmann Machines for shift-invariant feature learning , 2009, CVPR.
[2] Thomas Hofmann,et al. Greedy Layer-Wise Training of Deep Networks , 2007 .
[3] Geoffrey E. Hinton. Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.
[4] Alan F. Murray,et al. Synaptic Rewiring for Topographic Map Formation , 2008, ICANN.
[5] Sven Behnke,et al. Hierarchical Neural Networks for Image Interpretation , 2003, Lecture Notes in Computer Science.
[6] Graham W. Taylor,et al. Deconvolutional networks , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[7] Honglak Lee,et al. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations , 2009, ICML '09.
[8] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[9] Luca Maria Gambardella,et al. High-Performance Neural Networks for Visual Object Classification , 2011, ArXiv.
[10] Luca Maria Gambardella,et al. Flexible, High Performance Convolutional Neural Networks for Image Classification , 2011, IJCAI.
[11] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[12] Marc'Aurelio Ranzato,et al. Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Sven Behnke,et al. Hierarchical Neural Networks for Image Interpretation (Lecture Notes in Computer Science) , 2003 .
[14] Jürgen Schmidhuber,et al. Semilinear Predictability Minimization Produces Well-Known Feature Detectors , 1996, Neural Computation.
[15] Gökhan BakIr,et al. Predicting Structured Data , 2008 .
[16] Kunihiko Fukushima,et al. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position , 1980, Biological Cybernetics.
[17] Jürgen Schmidhuber,et al. Learning Factorial Codes by Predictability Minimization , 1992, Neural Computation.
[18] David G. Lowe,et al. Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[19] Geoffrey E. Hinton,et al. Modeling pixel means and covariances using factorized third-order boltzmann machines , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[20] A. Krizhevsky. Convolutional Deep Belief Networks on CIFAR-10 , 2010 .
[21] Sven Behnke,et al. Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition , 2010, ICANN.
[22] Marc'Aurelio Ranzato,et al. Sparse Feature Learning for Deep Belief Networks , 2007, NIPS.
[23] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[24] Patrice Y. Simard,et al. Best practices for convolutional neural networks applied to visual document analysis , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..
[25] Fu Jie Huang,et al. A Tutorial on Energy-Based Learning , 2006 .
[26] Peter Glöckner,et al. Why Does Unsupervised Pre-training Help Deep Learning? , 2013 .
[27] Honglak Lee,et al. An Analysis of Single-Layer Networks in Unsupervised Feature Learning , 2011, AISTATS.
[28] Jürgen Schmidhuber,et al. Feature Extraction Through LOCOCODE , 1999, Neural Computation.
[29] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[30] Thomas Serre,et al. Object recognition with features inspired by visual cortex , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[31] D. Hubel,et al. Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.