Derived Distance : towards a mathematical theory of visual cortex
暂无分享,去创建一个
Tomaso Poggio | Jake V. Bouvrie | Andrea Caponnetto | S. Smale | T. Poggio | A. Caponnetto | J. Bouvrie | Steve Smale
[1] David I. Perrett,et al. Neurophysiology of shape processing , 1993, Image Vis. Comput..
[2] Heiko Wersing,et al. Learning Optimized Features for Hierarchical Models of Invariant Object Recognition , 2003, Neural Computation.
[3] Keiji Tanaka,et al. Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. , 1994, Journal of neurophysiology.
[4] Michel Vidal-Naquet,et al. Visual features of intermediate complexity and their use in classification , 2002, Nature Neuroscience.
[5] E. Rolls,et al. INVARIANT FACE AND OBJECT RECOGNITION IN THE VISUAL SYSTEM , 1997, Progress in Neurobiology.
[6] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[7] R. Desimone. Face-Selective Cells in the Temporal Cortex of Monkeys , 1991, Journal of Cognitive Neuroscience.
[8] Thomas Serre,et al. A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual Cortex , 2005 .
[9] T. Poggio,et al. Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.
[10] D. Hubel,et al. Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.
[11] Thomas Serre,et al. A feedforward architecture accounts for rapid categorization , 2007, Proceedings of the National Academy of Sciences.
[12] N. Logothetis,et al. Shape representation in the inferior temporal cortex of monkeys , 1995, Current Biology.
[13] Simon J. Thorpe,et al. Ultra-Rapid Scene Categorization with a Wave of Spikes , 2002, Biologically Motivated Computer Vision.
[14] 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.
[15] Bartlett W. Mel. SEEMORE: Combining Color, Shape, and Texture Histogramming in a Neurally Inspired Approach to Visual Object Recognition , 1997, Neural Computation.
[16] Thomas Serre,et al. Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[17] Thomas Serre,et al. A quantitative theory of immediate visual recognition. , 2007, Progress in brain research.
[18] Y. Amit,et al. An integrated network for invariant visual detection and recognition , 2003, Vision Research.
[19] S. Smale,et al. On a model of visual cortex: learning invariance and selectivity , 2008 .
[20] 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).
[21] Keiji Tanaka,et al. Inferotemporal cortex and object vision. , 1996, Annual review of neuroscience.
[22] T. Poggio,et al. The Mathematics of Learning: Dealing with Data , 2005, 2005 International Conference on Neural Networks and Brain.