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Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition.
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M. Jaderberg, A. Vedaldi, and A. Zisserman · 2014
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Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition
C. F. Cadieu, H. Hong, D. L. K. Yamins, N. Pinto, D. Ardila, E. A. Solomon, N. J. Majaj, and J. J. DiCarlo · 2014
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Deep convolutional filter banks for texture recognition and segmentation
M. Cimpoi, S. Maji, and A. Vedaldi · 2014
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Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
E. L. Denton, W. Zaremba, J. Bruna, Y. LeCun, and R. Fergus · 2014
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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan and A. Zisserman · 2014
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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 · 2014
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Performance-optimized hierarchical models predict neural responses in higher visual cortex
D. L. K. Yamins, H. Hong, C. F. Cadieu, E. A. Solomon, D. Seibert, and J. J. DiCarlo · 2014
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Representation of naturalistic image structure in the primate visual cortex
A. J. Movshon and E. P. Simoncelli · 2015
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Image statistics underlying natural texture selectivity of neurons in macaque V4
G. Okazawa, S. Tajima, and H. Komatsu · 2015
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