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Normalization techniques have only recently begun to be exploited in supervised learning tasks.
Role of Inhibition in the Specification of Orientation Selectivity of Cells in the Cat Striate Cortex
Bonds, A. B · 1989
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Normalization of cell responses in cat striate cortex
Heeger, D. J · 1992
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A model of neuronal responses in visual area MT
Simoncelli, E. P. and Heeger, D. J · 1998
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A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
Martin, David, Fowlkes, Charless, Tal, Doron, and Malik, Jitendra · 2001
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Natural signal statistics and sensory gain control
Schwartz, O. and Simoncelli, E. P · 2001
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Image quality assessment: from error visibility to structural similarity
Wang, Zhou, Bovik, Alan C, Sheikh, Hamid R, and Simoncelli, Eero P · 2004
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Nonlinear image representation for efficient perceptual coding
Malo, J., Epifanio, I., Navarro, R., and Simoncelli, E. P · 2006
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Neural Computation , 20(10):2526–63, 2008
Sparse coding via thresholding and local competition in neural circuits · 2008
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Reducing statistical dependencies in natural signals using radial Gaussianization
Lyu, Siwei and Simoncelli, Eero P · 2008
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Why is Real-World Visual Object Recognition Hard?
Pinto, N., Cox, D. D., and DiCarlo, J. J · 2008
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The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction
Sinz, Fabian H and Bethge, Matthias · 2008
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Representation of Concurrent Stimuli by Population Activity in Visual Cortex
Busse, L., Wade, A. R., and Carandini, M · 2009
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Imagenet: A large-scale hierarchical image database
Deng, Jia, Dong, Wei, Socher, Richard, Li, Li-Jia, Li, Kai, and Fei-Fei, Li · 2009
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What is the best multi-stage architecture for object recognition?
Jarrett, K., Kavukcuoglu, K., Ranzato, M. A., and LeCun, Y · 2009
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Learning invariant features through topographic filter maps
Kavukcuoglu, K., Ranzato, M.’A., Fergus, R., and LeCun, Y · 2009
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The normalization model of attention
Reynolds, J. H. and Heeger, D. J · 2009
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Population coding under normalization
Ringach, D. L · 2009
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Perceptual organization in the tilt illusion
Schwartz, O., J., Sejnowski T., and P., Dayan · 2009
Cited alongside, same era.
Divisive Normalization in Olfactory Population Codes
Olsen, S. R, Bhandawat, V., and Wilson, R. I · 2010
Cited alongside, same era.
On single image scale-up using sparse-representations
Zeyde, Roman, Elad, Michael, and Protter, Matan · 2010
Cited alongside, same era.
Marginalization in Neural Circuits with Divisive Normalization
Beck, J. M., Latham, P. E., and Pouget, A · 2011
Cited alongside, same era.
Deep sparse rectifier neural networks
Glorot, Xavier, Bordes, Antoine, and Bengio, Yoshua · 2011
Cited alongside, same era.
Low-complexity single-image super-resolution based on nonnegative neighbor embedding
Bevilacqua, Marco, Roumy, Aline, Guillemot, Christine, and Morel, Marie-Line Alberi · 2012
Cited alongside, same era.
Reducing overfitting in deep networks by decorrelating representations
Cogswell, Michael, Ahmed, Faruk, Girshick, Ross, Zitnick, Larry, and Batra, Dhruv · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, Sergey and Szegedy, Christian · 2015
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Batch normalized recurrent neural networks
Laurent, César, Pereyra, Gabriel, Brakel, Philémon, Zhang, Ying, and Bengio, Yoshua · 2015
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Tensorflow: A system for large-scale machine learning
Abadi, Martín, Barham, Paul, Chen, Jianmin, Chen, Zhifeng, Davis, Andy, Dean, Jeffrey, Devin, Matthieu, Ghemawat, Sanjay, Irving, Geoffrey, Isard, Michael, Kudlur, Manjunath, Levenberg, Josh, Monga, Rajat, Moore, Sherry, Murray, Derek Gordon, Steiner, Benoit, Tucker, Paul A., Vasudevan, Vijay, Warden, Pete, Wicke, Martin, Yu, Yuan, and Zhang, Xiaoqiang · 2016
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Normalization as a canonical neural computation
Carandini, M. and Heeger, D. J · 2012
Cited alongside, same era.
ImageNet Classification with Deep Convolutional Neural Networks
Krizhevsky, A., Sutskever, I., and Hinton, G. E · 2012
Cited alongside, same era.
Convolutional neural networks applied to house numbers digit classification
Sermanet, P., Chintala, S., and LeCun, Y · 2012
Cited alongside, same era.
Building high-level features using large scale unsupervised learning
Le, Quoc V · 2013
Cited alongside, same era.
Temporal Adaptation Enhances Efficient Contrast Gain Control on Natural Images
Sinz, Fabian and Bethge, Matthias · 2013
Cited alongside, same era.
Anchored neighborhood regression for fast example-based super-resolution
Timofte, Radu, De Smet, Vincent, and Van Gool, Luc · 2013
Cited alongside, same era.
Ba, Jimmy Lei, Kiros, Jamie Ryan, and Hinton, Geoffrey E · 2016
Closest in time.
Density modeling of images using a generalized normalization transformation
Ballé, Johannes, Laparra, Valero, and Simoncelli, Eero P · 2016
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Cooijmans, Tim, Ballas, Nicolas, Laurent, César, and Courville, Aaron · 2016
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Image super-resolution using deep convolutional networks
Dong, Chao, Loy, Chen Change, He, Kaiming, and Tang, Xiaoou · 2016
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Image style transfer using convolutional neural networks
Gatys, Leon A., Ecker, Alexander S., and Bethge, Matthias · 2016
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Deep learning
Goodfellow, Ian, Bengio, Yoshua, and Courville, Aaron · 2016
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Deep residual learning for image recognition
He, Kaiming, Zhang, Xiangyu, Ren, Shaoqing, and Sun, Jian · 2016
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Early Visual Concept Learning with Unsupervised Deep Learning
Higgins, I., Matthey, L., Glorot, X., Pal, A., Uria, B., Blundell, C., Mohamed, S., and Lerchner, A · 2016
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Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex
Liao, Q. and Poggio, T · 2016
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Weight normalization: A simple reparameterization to accelerate training of deep neural networks
Salimans, Tim and Kingma, Diederik P · 2016
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Group sparse regularization for deep neural networks
Scardapane, S., Comminiello, D., Hussain, A., and Uncin, A · 2016
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Instance normalization: The missing ingredient for fast stylization
Ulyanov, Dmitry, Vedaldi, Andrea, and Lempitsky, Victor S · 2016
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