A Bayesian inference theory of attention: neuroscience and algorithms
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[1] Krista A. Ehinger,et al. Modelling search for people in 900 scenes: A combined source model of eye guidance , 2009 .
[2] D. Heeger,et al. The Normalization Model of Attention , 2009, Neuron.
[3] Christof Koch,et al. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .
[4] Shimon Ullman,et al. Image interpretation by a single bottom-up top-down cycle , 2008, Proceedings of the National Academy of Sciences.
[5] Tim K Marks,et al. SUN: A Bayesian framework for saliency using natural statistics. , 2008, Journal of vision.
[6] Nuno Vasconcelos,et al. Bottom-up saliency is a discriminant process , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[7] Tomaso Poggio,et al. Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex , 2007, The Journal of Neuroscience.
[8] T. Poggio,et al. A model of V4 shape selectivity and invariance. , 2007, Journal of neurophysiology.
[9] Liqing Zhang,et al. Saliency Detection: A Spectral Residual Approach , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[10] Thomas Serre,et al. A feedforward architecture accounts for rapid categorization , 2007, Proceedings of the National Academy of Sciences.
[11] E. Miller,et al. Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices , 2007, Science.
[12] Thomas Serre,et al. Robust Object Recognition with Cortex-Like Mechanisms , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[13] Jeremy M. Wolfe,et al. Guided Search 4.0: Current Progress With a Model of Visual Search , 2007, Integrated Models of Cognitive Systems.
[14] John F. Kalaska,et al. Computational neuroscience : theoretical insights into brain function , 2007 .
[15] Christof Koch,et al. Attention in hierarchical models of object recognition. , 2007, Progress in brain research.
[16] Pietro Perona,et al. Graph-Based Visual Saliency , 2006, NIPS.
[17] L. Zhaoping,et al. A theory of a saliency map in primary visual cortex (V1) tested by psychophysics of colour–orientation interference in texture segmentation , 2006 .
[18] Laurent Itti,et al. An Integrated Model of Top-Down and Bottom-Up Attention for Optimizing Detection Speed , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[19] 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 .
[20] John K. Tsotsos,et al. Saliency Based on Information Maximization , 2005, NIPS.
[21] John K. Tsotsos,et al. Neurobiology of Attention , 2005 .
[22] Rajesh P. N. Rao,et al. Bayesian inference and attentional modulation in the visual cortex , 2005, Neuroreport.
[23] Tomaso Poggio,et al. Fast Readout of Object Identity from Macaque Inferior Temporal Cortex , 2005, Science.
[24] Nuno Vasconcelos,et al. Integrated learning of saliency, complex features, and object detectors from cluttered scenes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[25] Robert Desimone,et al. Parallel and Serial Neural Mechanisms for Visual Search in Macaque Area V4 , 2005, Science.
[26] Yuanzhen Li,et al. Feature congestion: a measure of display clutter , 2005, CHI.
[27] Peter Dayan,et al. Inference, Attention, and Decision in a Bayesian Neural Architecture , 2004, NIPS.
[28] F. Fleuret. Fast Binary Feature Selection with Conditional Mutual Information , 2004, J. Mach. Learn. Res..
[29] Minami Ito,et al. Representation of Angles Embedded within Contour Stimuli in Area V2 of Macaque Monkeys , 2004, The Journal of Neuroscience.
[30] E. Rolls,et al. A Neurodynamical cortical model of visual attention and invariant object recognition , 2004, Vision Research.
[31] Kunihiko Fukushima,et al. A neural network model for selective attention in visual pattern recognition , 1986, Biological Cybernetics.
[32] 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.
[33] Antonio Torralba,et al. Top-down control of visual attention in object detection , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).
[34] Jay Hegdé,et al. How Selective Are V1 Cells for Pop-Out Stimuli? , 2003, The Journal of Neuroscience.
[35] Y. Amit,et al. An integrated network for invariant visual detection and recognition , 2003, Vision Research.
[36] Antonio Torralba,et al. Modeling global scene factors in attention. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[37] Tai Sing Lee,et al. Hierarchical Bayesian inference in the visual cortex. , 2003, Journal of the Optical Society of America. A, Optics, image science, and vision.
[38] Katherine M. Armstrong,et al. Selective gating of visual signals by microstimulation of frontal cortex , 2003, Nature.
[39] M. Goldberg,et al. Neuronal Activity in the Lateral Intraparietal Area and Spatial Attention , 2003, Science.
[40] S. Hochstein,et al. View from the Top Hierarchies and Reverse Hierarchies in the Visual System , 2002, Neuron.
[41] Thomas Serre,et al. On the Role of Object-Specific Features for Real World Object Recognition in Biological Vision , 2002, Biologically Motivated Computer Vision.
[42] Simon J. Thorpe,et al. Ultra-Rapid Scene Categorization with a Wave of Spikes , 2002, Biologically Motivated Computer Vision.
[43] S. Treue,et al. Attentional Modulation Strength in Cortical Area MT Depends on Stimulus Contrast , 2002, Neuron.
[44] Michel Vidal-Naquet,et al. Visual features of intermediate complexity and their use in classification , 2002, Nature Neuroscience.
[45] Rajesh P. N. Rao,et al. Probabilistic Models of the Brain: Perception and Neural Function , 2002 .
[46] C. Connor,et al. Shape representation in area V4: position-specific tuning for boundary conformation. , 2001, Journal of neurophysiology.
[47] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[48] F. Velde,et al. From Knowing What to Knowing Where: Modeling Object-Based Attention with Feedback Disinhibition of Activation , 2001 .
[49] C. Koch,et al. Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.
[50] S. Thorpe,et al. A Limit to the Speed of Processing in Ultra-Rapid Visual Categorization of Novel Natural Scenes , 2001, Journal of Cognitive Neuroscience.
[51] F. van der Velde,et al. From Knowing What to Knowing Where: Modeling Object-Based Attention with Feedback Disinhibition of Activation , 2001, Journal of Cognitive Neuroscience.
[52] Edmund T. Rolls,et al. A Model of Invariant Object Recognition in the Visual System: Learning Rules, Activation Functions, Lateral Inhibition, and Information-Based Performance Measures , 2000, Neural Computation.
[53] Takeo Kanade,et al. A statistical method for 3D object detection applied to faces and cars , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[54] R. Desimone,et al. Attention Increases Sensitivity of V4 Neurons , 2000, Neuron.
[55] J. Hegdé,et al. Selectivity for Complex Shapes in Primate Visual Area V2 , 2000, The Journal of Neuroscience.
[56] T. Poggio,et al. Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.
[57] R. Rosenholtz. A simple saliency model predicts a number of motion popout phenomena , 1999, Vision Research.
[58] Stefan Treue,et al. Feature-based attention influences motion processing gain in macaque visual cortex , 1999, Nature.
[59] R. Desimone,et al. Competitive Mechanisms Subserve Attention in Macaque Areas V2 and V4 , 1999, The Journal of Neuroscience.
[60] Carrie J. McAdams,et al. Effects of Attention on Orientation-Tuning Functions of Single Neurons in Macaque Cortical Area V4 , 1999, The Journal of Neuroscience.
[61] M. Goldberg,et al. Space and attention in parietal cortex. , 1999, Annual review of neuroscience.
[62] R. Zemel,et al. Statistical models and sensory attention , 1999 .
[63] R. Desimone. Visual attention mediated by biased competition in extrastriate visual cortex. , 1998, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[64] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[65] J. Movshon,et al. Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex , 1997, The Journal of Neuroscience.
[66] John K. Tsotsos. Limited Capacity of Any Realizable Perceptual System Is a Sufficient Reason for Attentive Behavior , 1997, Consciousness and Cognition.
[67] Bartlett W. Mel. SEEMORE: Combining Color, Shape, and Texture Histogramming in a Neurally Inspired Approach to Visual Object Recognition , 1997, Neural Computation.
[68] D. C. Essen,et al. Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey. , 1996, Journal of neurophysiology.
[69] Keiji Tanaka,et al. Inferotemporal cortex and object vision. , 1996, Annual review of neuroscience.
[70] J. Duncan. Target and nontarget grouping in visual search , 1995, Perception & psychophysics.
[71] Leslie G. Ungerleider,et al. ‘What’ and ‘where’ in the human brain , 1994, Current Opinion in Neurobiology.
[72] David I. Perrett,et al. Neurophysiology of shape processing , 1993, Image Vis. Comput..
[73] Keiji Tanaka,et al. Coding visual images of objects in the inferotemporal cortex of the macaque monkey. , 1991, Journal of neurophysiology.
[74] D. J. Felleman,et al. Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.
[75] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[76] I. Biederman. Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.
[77] R. Desimone,et al. Visual properties of neurons in area V4 of the macaque: sensitivity to stimulus form. , 1987, Journal of neurophysiology.
[78] S Ullman,et al. Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.
[79] M. Posner,et al. Components of visual orienting , 1984 .
[80] I. Biederman,et al. Scene perception: Detecting and judging objects undergoing relational violations , 1982, Cognitive Psychology.
[81] J. Daugman. Two-dimensional spectral analysis of cortical receptive field profiles , 1980, Vision Research.
[82] A. Treisman,et al. A feature-integration theory of attention , 1980, Cognitive Psychology.
[83] D. Hubel,et al. Receptive fields and functional architecture of monkey striate cortex , 1968, The Journal of physiology.
[84] A. L. I︠A︡rbus. Eye Movements and Vision , 1967 .
[85] A. L. Yarbus,et al. Eye Movements and Vision , 1967, Springer US.
[86] D. Hubel,et al. Receptive fields of single neurones in the cat's striate cortex , 1959, The Journal of physiology.
[87] J. Deutsch. Perception and Communication , 1958, Nature.