Color-opponent receptive fields derived from independent component analysis of natural images
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[1] N. Daw. Colour‐coded ganglion cells in the goldfish retina: extension of their receptive fields by means of new stimuli , 1968, The Journal of physiology.
[2] D. Hubel,et al. Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.
[3] B. Dow. Functional classes of cells and their laminar distribution in monkey visual cortex. , 1974, Journal of neurophysiology.
[4] P Gouras,et al. Opponent‐colour cells in different layers of foveal striate cortex , 1974, The Journal of physiology.
[5] C. R. Michael. Color vision mechanisms in monkey striate cortex: dual-opponent cells with concentric receptive fields. , 1978, Journal of neurophysiology.
[6] C. R. Michael. Color-sensitive complex cells in monkey striate cortex. , 1978, Journal of neurophysiology.
[7] C. R. Michael,et al. Columnar organization of color cells in monkey's striate cortex. , 1981, Journal of neurophysiology.
[8] G. Buchsbaum,et al. Trichromacy, opponent colours coding and optimum colour information transmission in the retina , 1983, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[9] D. Hubel,et al. Anatomy and physiology of a color system in the primate visual cortex , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[10] D. Ts'o,et al. The organization of chromatic and spatial interactions in the primate striate cortex , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[11] R. Desimone,et al. Spectral properties of V4 neurons in the macaque , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[12] P. Lennie,et al. Chromatic mechanisms in striate cortex of macaque , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[13] Gershon Buchsbaum,et al. A computational model of spatiochromatic image coding in early vision , 1991, J. Vis. Commun. Image Represent..
[14] S. Zeki. A vision of the brain , 1993 .
[15] David J. Field,et al. What Is the Goal of Sensory Coding? , 1994, Neural Computation.
[16] Leif H. Finkel,et al. Network simulations of retinal and cortical contributions to color constancy , 1995, Vision Research.
[17] Harry G. Barrow,et al. A Self-Organizing Model of Color Blob Formation , 1996, Neural Computation.
[18] S. Engel,et al. Colour tuning in human visual cortex measured with functional magnetic resonance imaging , 1997, Nature.
[19] D. Kiper,et al. Chromatic properties of neurons in macaque area V2 , 1997, Visual Neuroscience.
[20] H B Barlow,et al. The knowledge used in vision and where it comes from. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[21] Terrence J. Sejnowski,et al. The “independent components” of natural scenes are edge filters , 1997, Vision Research.
[22] J. V. van Hateren,et al. Independent component filters of natural images compared with simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[23] Te-Won Lee,et al. Independent Component Analysis , 1998, Springer US.
[24] T Troscianko,et al. Color and luminance information in natural scenes. , 1998, Journal of the Optical Society of America. A, Optics, image science, and vision.
[25] D. Ruderman,et al. Estimation of errors in luminance signals encoded by primate retina resulting from sampling of natural images with red and green cones. , 1998, Journal of The Optical Society of America A-optics Image Science and Vision.
[26] D. Ruderman,et al. Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[27] Terrence J. Sejnowski,et al. Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.
[28] Terrence J. Sejnowski,et al. Unsupervised Learning , 2018, Encyclopedia of GIS.