Full Fist of related bibliographies

related bibliography on edge detection

  • David Marr, Ellen Hildreth. Theory of edge detection. Proceedings of the Royal Society of London. Series B, Biological Sciences, 207:187-217, 1980 abstract.
  • Peter J. Burt, Edward H. Adelson. The Laplacian Pyramid as a compact image code. IEEE Transactions on Communications, COM-31,4:532--40, 1983 abstract.
  • J. Canny. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 8:679-98, 1986 abstract.
  • Rachid Deriche. Using Canny's criteria to derive a recusively implemented optimal edge detector. International Journal of Computer Vision, :167-87, 1987 abstract.
  • Rachid Deriche. Fast Algorithms for Low-Level Vision. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 1(12):78--8, 1990 abstract.
  • S. Castan, J. Zhao, J. Shen. Optimal Filter for Edge Detection Methods and Results. In In Proceedings of the First European Conference on Computer Vision (Eccv), pages 13-7. 1990 abstract.
  • Stéphane Mallat, Sifen Zhong. Wavelet Transform Maxima and Multiscale Edge. In Wavelets and Their Applications, pages 67--104. Jones and Bartlett Publishers, 1992 abstract.
  • Stéphane Mallat, Sifen Zhong. Characterization of Signals from Multiscale Edges. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 14(7):710--32, 1992 abstract.
  • Anthony J. Bell, Terrence J. Sejnowski. The `independent components' of natural scenes are edge filters. Vision Research, 37(23):3327--38, 1997 abstract.
  • K. R. Popper. All Life Is Problem Solving. Routledge, London, 1999.
  • Charles Poynton. Frequently Asked Questions about Gamma. 1999.
  • Antonio Turiel, Néstor Parga. The multifractal structure of contrast changes in natural images: from sharp edges to textures.. Neural Computation, 12:763--93, 2000 abstract.
  • Wilson S. Geisler, J. S. Perry, B. J. Super, D. P. Gallogly. Edge co-occurance in natural images predicts contour grouping performance.. Vision Research, 41(6):711-24, 2001 abstract.
  • Guillaume S. Masson, L.S. Stone. From following edges to pursuing objects, URL . Journal of Neurophysiology, 88(5):2869--73, 2002 abstract.
  • Antonio Turiel, Angela del Pozo. Reconstructing images from their most singular fractal manifold. IEEE Transactions in Image Processing, 11(4):345--50, 2002 abstract.
  • Jean Petitot. The neurogeometry of pinwheels as a sub-Riemannian contact structure, URL . Journal of Physiology (Paris), 97(2-3):265--309, 2003 abstract.
  • Sylvain Fischer, Rafael Redondo, Laurent Perrinet, Gabriel Crist\'obal. Efficient representation of natural images using local cooperation. In Perception, pages 241. 2005 abstract.
  • Sylvain Fischer, Rafael Redondo, Laurent Perrinet, Gabriel Crist\'obal. Sparse Gabor wavelets by local operations. In Proceedings SPIE, pages 75--86. 2005 abstract.
  • Rafael Redondo, Sylvain Fischer, Laurent Perrinet, Gabriel Crist\'obal. Modeling of simple cells through a sparse overcomplete gabor wavelet representation based on local inhibition and facilitation. In Perception, pages 238. 2005 abstract.
  • Sylvain Fischer, Gabriel Crist\'obal, Rafael Redondo. Sparse Overcomplete Gabor Wavelet Representation Based on Local Competitions. IEEE Transactions in Image Processing, 15(2):265, 2006 abstract.
  • Laurent Perrinet, Frédéric V. Barthélemy, Guillaume S. Masson. Input-output transformation in the visuo-oculomotor loop: modeling the ocular following response to center-surround stimulation in a probabilistic framework. In 1ère conférence francophone NEUROsciences COMPutationnelles - NeuroComp, 2006 abstract.
  • Sylvain Fischer, Rafael Redondo, Laurent Perrinet, Gabriel Crist\'obal. Sparse approximation of images inspired from the functional architecture of the primary visual areas, URL . EURASIP Journal on Advances in Signal Processing, 2007(1):122, 2007 abstract.
  • Sylvain Fischer, Filip Sroubek, Laurent Perrinet, Rafael Redondo, Gabriel Crist\'obal. Self-invertible 2D log-Gabor wavelets. International Journal of Computer Vision, 2007 abstract.

related bibliography on Matching Pursuit

  • Stéphane Mallat, Zhifeng Zhang. Matching Pursuit with time-frequency dictionaries. IEEE Transactions on Signal Processing, 41(12):3397-3414, 1993 abstract.
  • Y. Pati, R. Rezaiifar, P. Krishnaprasad. Orthogonal Matching Pursuit: Recursive Function Approximation with Applications to Wavelet Decomposition. In Proceedings of the 27 th Annual Asilomar Conference on Signals, Systems, and Computers, 1993 abstract.
  • K. J. Blinowska, P. J. Durka. The Application of Wavelet Transform and Matching Pursuit to the Time-Varying EEG signals. In Intelligent Engineering Systems through Artificial Neural Networks, pages 535-540. ASME Press, New York, 1994 abstract.
  • Shaobing Chen, David L. Donoho. Basis pursuit. In 28th Asilomar Conference on Signal, Systems and Computers, 1994 abstract.
  • Geoffrey Davis. Adaptive Nonlinear Approximations.. 1994 abstract.
  • Francois Bergeaud, Stéphane Mallat, F. Bergeaud, Stéphane Mallat. Matching pursuit of images. pages 53--56. 1995 abstract.
  • Shaobing Chen. Basis pursuit. 1995 abstract.
  • R. Neff, A. Zakhor. Very Low Bit-Rate Video Coding based on Matching Pursuits. IEEE Transactions on CSVT, 7(5):158--71, 1997 abstract.
  • P. J. Durka, D. Ircha, K. J. Blinowska. Stochastic time-frequency dictionaries for matching pursuit. IEEE Transactions on Signal Processing, 49(3):507--510, 2001 abstract.
  • Pierre Frossard, Pierre Vandergheynst. A Posteriori Quantized Matching Pursuit. IEEE Data Compression Conference, 2001 abstract.
  • Laura Rebollo-Neira, David Lowe. Optimized orthogonal matching pursuit approach. IEEE Signal Processing Letters, 9(4):137--40, 2002 abstract.
  • Laurent Perrinet, Manuel Samuelides, Simon J. Thorpe. Sparse spike coding in an asynchronous feed-forward multi-layer neural network using Matching Pursuit., URL . Neurocomputing, 57C:125--34, 2002, abstract.
  • Michael S. Lewicki. Efficient coding of natural sounds, URL . Nature Neuroscience, 5(4):356--62, 2002 abstract.
  • Enrico Capobianco. Independent multiresolution component analysis and matching pursuit, URL . Comput. Stat. Data Anal., 42(3):385--402, 2003 abstract.
  • Laurent Perrinet. Comment déchiffrer le code impulsionnel de la vision ? Étude du flux parallèle, asynchrone et épars dans le traitement visuel ultra-rapide, URL . 2003, abstract.
  • Miroslav Andrle, Laura Rebollo-Neira, Evangelos Sagianos. Backward Optimized Orthogonal Matching Pursuit. Arxiv preprint, :math/0401279, 2004 abstract.
  • Laurent Perrinet. Feature detection using spikes : the greedy approach., URL URL2 URL3 . Journal of Physiology (Paris), 98(4-6):530--9, 2004 abstract.
  • Laurent Perrinet, Manuel Samuelides, Simon J. Thorpe. Coding static natural images using spiking event times: do neurons cooperate?, URL URL2 URL3 URL4 . IEEE Transactions on Neural Networks, 15(5):1164--75, 2004 abstract.
  • Sylvain Fischer, Rafael Redondo, Laurent Perrinet, Gabriel Crist\'obal. Efficient representation of natural images using local cooperation. In Perception, pages 241. 2005 abstract.
  • R. Gribonval, P. Vandergheynst. On the exponential convergence of matching pursuits in quasi-incoherent dictionaries, URL URL2 . IEEE Transactions in Information Theory, :255- -61, 2006 abstract.
  • Sylvain Fischer, Gabriel Crist\'obal, Rafael Redondo. Sparse Overcomplete Gabor Wavelet Representation Based on Local Competitions. IEEE Transactions in Image Processing, 15(2):265, 2006 abstract.
  • Evan C. Smith, Michael S. Lewicki. Efficient Auditory Coding, URL . Nature, 439(7079):978--82, 2006 abstract.
  • Laurent Perrinet, Jens Kremkow. Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex. In The Functional Architecture of the Brain : from Dendrites to Networks. Symposium in honour of Dr Suzanne Tyc-Dumont. 4- 5 May 2006. GLM, Marseille, France, 2006 abstract.
  • Bruno Cessac, Manuel Samuelides. From neuron to neural networks dynamics, URL URL2 . pages 7--88. abstract.
  • Laurent Perrinet. Dynamical Neural Networks: modeling low-level vision at short latencies, URL . pages 163--225. abstract.
  • Laurent Perrinet. Neural Codes for Adaptive Sparse Representations of Natural Images, URL URL2 . In Mathematical image processing meeting (Marseille, France) September 5, 2007, 2007 abstract.
  • Thomas Blumensath, Mike E. Davies. Gradient Pursuits. 2007 abstract.
  • Thomas Blumensath, Mike E. Davies. Iterative Thresholding for Sparse Approximations. The Journal of Fourier Analysis and Applications, 2007 abstract.
  • Thomas Blumensath, Michael E. Davies. Rate-Distortion Analysis of Sparse Overcomplete Codes. 2007 abstract.
  • Laurent Perrinet. Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images, URL URL2 URL3 . In Optical and Digital Image Processing Conference 7000 - Proceedings of SPIE Volume 7000, 7 - 11 April 2008, pages 70000F. SPIE, 2008 abstract.
  • Laurent Perrinet. Role of homeostasis in learning sparse representations, URL . Neural Computation, 2010 abstract.

related bibliography on Rank-Order Coding

  • Edgar Adrian. The basis of sensation: the action of sense organs. London: ChristoPhers., 1928.
  • Simon J. Thorpe. Image processing by humans.. Technique et Science Informatiques, 7(6):517--25, 1988 abstract.
  • Simon J. Thorpe, M. Imbert. Biological constraints on connectionist modelling.. In Connectionism in Perspective, Pfeifer, R., Schreter, Z., Fogelman-Soulie, F., and Steels, L., eds., Elsevier (North-Holland), 1989 abstract.
  • Simon J. Thorpe. Spike arrival times: a highly efficient coding scheme for neural networks. Parallel processing in Neural Systems and Computers, :91-4, 1990 abstract.
  • Simon J. Thorpe, Michel Imbert. Parallel processing in neural systems.. R.Eckmiller G.Hartman and G.Hauske, North Holland, 1990.
  • S. Celebrini, Simon J. Thorpe, Y. Trotter, M. Imbert. Dynamics of orientation coding in area V1 of the awake primate.. Visual Neuroscience, 5(10):811-25, 1993 abstract.
  • Philippe Barbe, Marc Hallin. Statistiques de rang linéaires; normalité asymptotique et théorème de projection de H\`ajek. In Inferences non parametriques., Association pour la Statistique et ses Utilisations, 1995 abstract.
  • Simon J. Thorpe, Denis Fize, Catherine Marlot. Speed of processing in the human visual system. Nature, 381:520--2, 1996 abstract.
  • Simon J. Thorpe, Jacques Gautrais. Rapid Visual Processing using Spike Asynchrony. pages 901. abstract.
  • Jacques Gautrais, Simon J. Thorpe. Rate Coding vs. temporal order coding. Biosystems, 1997 abstract.
  • Manuel Samuelides, Simon J. Thorpe, E. Veneau. Implementing Hebbian Learning in a Rank-Based Neural Network. Lecture Notes in Computer Science., 1327:145--50, 1997 abstract.
  • Rufin van Rullen, Jacques Gautrais, Arnaud Delorme, Simon J. Thorpe. Face Processing Using One Spike Per Neuron.. BioSystems, 483:229--39, 1998 abstract.
  • Michèle Fabre-Thorpe, Guillaume Richard, Arnaud Delorme. Rapid Categoriztion of Natural Scenes by Rhesus Monkeys.. Neuroreport, (9):303-8, 1998 abstract.
  • Simon J. Thorpe, Jacques Gautrais. Rank Order Coding. In Computational Neuroscience: Trends in Research 1998, J. Bower, Editor. Plenum Press: New York., pages 113--8. 1998 abstract.
  • J. Vaccaro, D. Gourion, Manuel Samuelides, Simon J. Thorpe. Rank based hebbian learning in a multi-layered neural network.. In Proccedings of VI-DYNN'98. Royal Institute of Technology, Stockholm, Sweden., 1998 abstract.
  • Rufin van Rullen, Simon J. Thorpe. Spatial Attention in Asynchronous Neural Networks.. Neurocomputing, 26--7:911--8, 1999 abstract.
  • Arnaud Delorme, J. Gautrais, Rufin van Rullen, Simon J. Thorpe. SpikeNET: a simulator for modeling large networks of integrate and fire neurons.. Neurocomputing, 24:663-70, 1999 abstract.
  • Arnaud Delorme, Guillaume Richard, Michèle Fabre-Thorpe. Rapid processing of complex natural scenes: a role for the magnocellular pathway.. Neurocomputing, 26-7:663-70, 1999 abstract.
  • Rufin van Rullen, Arnaud Delorme, Simon J. Thorpe. Object recognition using spiking neurons II: Spatial attention explained by temporal precedence of information.. 2000 abstract.
  • Arnaud Delorme, Guillaume Richard, Michèle Fabre-Thorpe. Ultra-Rapid Categorization of Natural Scenes Does Not Rely on Colour Cues: A Study in Monkeys and Humans. Vision Research, 40(16):2187-200, 2000 abstract.
  • Simon J. Thorpe, Arnaud Delorme, Rufin van Rullen, William Paquier. Reverse engineering of the visual system using networks of spiking neurons.. In IEEE International Symposium on Circuits and Systems, pages 405--8. 2000 abstract.
  • Rufin van Rullen. Une premiere vague de potentiels d'action, une première vague idée de la scène visuelle. Role de l'asynchronie dans le traitement rapide de l'information visuelle.. 2001 abstract.
  • Rufin van Rullen, Arnaud Delorme, Simon J. Thorpe. Feed-forward contour integration in primary visual cortex based on asynchronous spike propagation.. Neurocomputing, 1--4(38--40):1003--9, 2001 abstract.
  • Rufin van Rullen, Simon J. Thorpe. Rate coding versus temporal order coding: what the retina ganglion cells tell the visual cortex. Neural Computation, 13(6):1255--83, 2001 abstract.
  • Arnaud Delorme. Traitement visuel rapide de scènes naturelles chez le singe, l'homme et la machine : une vision qui va de l'avant. 2001 abstract.
  • Arnaud Delorme, Simon J. Thorpe. SpikeNET: An Event-driven Simulation Package for Modeling Large Networks of Spiking Neurons. Network: Computation in Neural Systems, 14:613--27, 2001 abstract.
  • Arnaud Delorme, Simon J. Thorpe. Face processing using one spike per neuron: resistance to image degradation.. Neural Networks, 6-7(14):795-804, 2001 abstract.
  • Michèle Fabre-Thorpe, Arnaud Delorme, Catherine Marlot, Simon J. Thorpe. A Limit in the Speed of Processing in Ultra-Rapid Categorization of Novel Natural Scenes.. Journal of Cognitive Neuroscience, 13(2), 2001 abstract.
  • Mark C. W. van Rossum, Gina G. Turrigiano, Sacha B. Nelson. Fast Propagation of Firing Rates through Layered Networks of Noisy Neurons. Journal of Neuroscience, 22(5):1956--66, 2001 abstract.
  • Simon J. Thorpe, A. Delorme, Rufin van Rullen. Spike based strategies for rapid processing.. Neural Networks, 6-7(14):715-26, 2001 abstract.
  • Simon J. Thorpe, Michèle Fabre-Thorpe. Neuroscience. Seeking categories in the brain.. Science, 291(5502):260-263, 2001 abstract.
  • Simon J. Thorpe, KR Gegenfurtner, Michèle Fabre-Thorpe, HH Bülthoff. Detection of animals in natural images using far peripheral vision.. European Journal of Neuroscience, 14(5):869-76, 2001 abstract.
  • Arnaud Delorme, S. Makeig, Michèle Fabre-Thorpe, Terrence J. Sejnowski. From Single-trials EEG to Brain Area Dynamics. Neurocomputing, 2002 abstract.
  • Guillaume A. Rousselet, Michèle Fabre-Thorpe, Simon J. Thorpe. Two unrelated natural scenes can be processed as fast as one.. ECVP 2001. Supplement., 2002 abstract.
  • Michael S. Lewicki. Efficient coding of natural sounds, URL . Nature Neuroscience, (4):356--62, 2002 abstract.
  • Evan C. Smith, Michael S. Lewicki. Efficient Auditory Coding, URL . Nature, 439(7079):978--82, 2006 abstract.
  • Basabdatta Sen, Steve Furber. Information Recovery from Rank-Order Encoded Images. In Workshop on Biologically Inspired Information Fusion University of Surrey, 2006 abstract.
  • Goded Shahaf, Danny Eytan, Asaf Gal, Einat Kermany, Vladimir Lyakhov, Christoph Zrenner, Shimon Marom. Order-Based Representation in Random Networks of Cortical Neurons, URL URL2 . PLoS Computational Biology, 4(11):e1000228+, 2008 abstract.

related bibliography on Dynamical Neural Networks

  • Bruno Cessac, Manuel Samuelides. From neuron to neural networks dynamics, URL . pages 7--88. abstract.
  • Laurent U. Perrinet. Dynamical Neural Networks: modeling low-level vision at short latencies, URL . pages 163--225. abstract.
  • Bruno Cessac, Emmanuel Daucé, Laurent U. Perrinet, Manuel Samuelides. Topics in Dynamical Neural Networks: From Large Scale Neural Networks to Motor Control and Vision, URL . Springer Verlag, Berlin / Heidelberg, 2007.

related bibliography on sparse coding

  • Peter Földi\'ak. Forming sparse representations by local anti-Hebbian learning. Biological Cybernetics, 64, 1990 abstract.
  • David L. Donoho, Iain M. Johnstone. Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3):425-55, 1994 abstract.
  • Colin Fyfe, Roland J Baddeley. Finding compact and sparse- distributed representations of visual images, URL URL2 URL3 . Network: Computation in Neural Systems, 6:333--44, 1995 abstract.
  • B. K. Natarajan. Sparse Approximate Solutions to Linear Systems. SIAM Journal of Computation, 24(2):227--34, 1995 abstract.
  • Bruno A. Olshausen. Learning linear, sparse, factorial codes. Technical report, MIT Artificial Intelligence Laboratory and Center For Biological And Computational Learning, Departement of brain and cognitive sciences, 1996.
  • Bruno A. Olshausen, David J. Field. Natural image statistics and efficient coding. Network: Computation in Neural Systems, 7:333--9, 1996 abstract.
  • Bruno A. Olshausen, David J. Field. Emergence of simple-cell receptive field properties by learning a sparse code for natural images.. Nature, 381(6583):607--9, 1996 abstract.
  • Bruno A. Olshausen, David J. Field. Sparse coding with an overcomplete basis set: a strategy employed by V1?. Vision Research, 37:3311--25, 1997 abstract.
  • Michael S. Lewicki, Bruno A. Olshausen. Probabilistic framework for the adaptation and comparison of image codes, URL URL2 . Journal of Optical Society of America, A, 16(7):1587--601, 1998 abstract.
  • Tomaso Poggio, Frederico Girosi. A Sparse Representation for Function Approximation. Neural Computation, 10(6):1445-1454, 1998 abstract.
  • Michael S. Lewicki, Terrence J. Sejnowski. Coding time-varying signals using sparse, shift-invariant representations.. abstract.
  • Bruno A. Olshausen, K. Jarrod Millman. Learning sparse codes with a mixture-of-Gaussians prior, URL URL2 URL3 . pages 887--93. abstract.
  • Bruno A. Olshausen, Phil Sallee, Michael S. Lewicki. Learning Sparse Codes using a Wavelet pyramid architecture. abstract.
  • Michael S. Lewicki, Terrence J. Sejnowski. Learning overcomplete representations, URL URL2 . Neural Computation, 12(2):337--65, 2000 abstract.
  • William E. Vinje, Jack L. Gallant. Sparse coding and decorrelation in primary visual cortex during natural vision, URL . Science, 287:1273-1276, 2000 abstract.
  • David L. Donoho, A G Flesia. Can recent innovations in harmonic analysis 'explain' key findings in natural image statistics?. Network: Computation in Neural Systems, 12(3):371--93, 2001 abstract.
  • B. Willmore, D. J. Tolhurst. Characterizing the sparseness of neural codes.. Network: Computation in Neural Systems, 12(3):255--270, 2001 abstract.
  • Arthur E. C. Pece. The problem of sparse image coding. Technical report, Institue of computer science, University of Copenhagen, 2001.
  • Martin J. Wainwright, Odelia Schwartz, Eero P. Simoncelli. Natural Image Statistics and Divisive Normalization: Modeling Nonlinearities and Adaptation in Cortical Neurons. In Statistical Theories of the Brain, The MIT Press, Rajesh Rao, Bruno Olshausen and M Lewicki, 2001 abstract.
  • Michael Zibulevsky, Barak A. Pearlmutter. Blind Source Separation by sparse decomposition. Neural Computation, 13(4):863--82, 2001 abstract.
  • Peter Földi\'ak. Sparse Coding in the primate cortex. pages 895-8. abstract.
  • C. Meunier, J.-P. Nadal. Sparsely coded neural networks. In The handbook of Brain Theory and Neural Networks, pages 899-901. abstract.
  • Bruno A. Olshausen. Sparse Codes and Spikes. pages 257--72. abstract.
  • Richard H. R. Hahnloser, Alexay A. Kozhevnikov, Michale S. Fee. An ultra-sparse code underlies the generation of neural sequences in a songbird. Nature, 419:65--70, 2002 abstract.
  • Patrik O. Hoyer, Aapo Hyvärinen. A Multi-layer Sparse Coding Network Learns Contour Coding from Natural Images. Vision Research, 42(12):1593--605, 2002 abstract.
  • Arthur E. C. Pece. The problem of sparse image coding. Journal of Mathematical Imaging and Vision, 17:89--108, 2002 abstract.
  • Laurent U. Perrinet, Manuel Samuelides. Sparse Image Coding Using an Asynchronous Spiking Neural Network. In Proceedings of ESANN, pages 313--8. 2002 abstract.
  • Laurent U. Perrinet, Manuel Samuelides. Visual Strategies for Sparse Spike Coding. In Actes de Neurosciences et Sciences de l'Ingenieur, L'Agelonde,, 2002 abstract.
  • Laurent U. Perrinet, Manuel Samuelides, Simon J. Thorpe. Sparse spike coding in an asynchronous feed-forward multi-layer neural network using Matching Pursuit., URL URL2 . Neurocomputing, 57C:125--34, 2002 abstract.
  • Michael S. Lewicki. Efficient coding of natural sounds, URL . Nature Neuroscience, 5(4):356--62, 2002 abstract.
  • Phil Sallee, Bruno A. Olshausen. Learning Sparse Multiscale Image Representations. pages 1327--34. abstract.
  • Enrico Capobianco. Independent multiresolution component analysis and matching pursuit, URL . Comput. Stat. Data Anal., 42(3):385--402, 2003 abstract.
  • Michael R. DeWeese, Michael Wehr, Anthony M. Zador. Binary coding in auditory cortex. Journal of Neuroscience, 23(21), 2003 abstract.
  • Laurent U. Perrinet, Manuel Samuelides, Simon J. Thorpe. Emergence of filters from natural scenes in a sparse spike coding scheme., URL URL2 . Neurocomputing, 58--60(C):821--6, 2003 abstract.
  • Bruno A. Olshausen, David J. Field. Sparse coding of sensory inputs. Current Opinion in Neurobiology, (14):481 87, 2004 abstract.
  • Laurent U. Perrinet. Finding Independent Components using spikes : a natural result of hebbian learning in a sparse spike coding scheme, URL URL2 URL3 URL4 . Natural Computing, 3(2):159--75, 2004 abstract.
  • Laurent U. Perrinet. Feature detection using spikes : the greedy approach., URL URL2 URL3 . Journal of Physiology (Paris), 98(4-6):530--9, 2004 abstract.
  • Li Zhao. Is sparse and distributed the coding goal of simple cells?, URL URL2 URL3 . Biological Cybernetics, 91(6):408-16, 2004 abstract.
  • D.B. Grimes, R.P.N. Rao. Bilinear Sparse Coding for Invariant Vision. Neural Computation, 17:47--73, 2005 abstract.
  • Erwan Le Pennec, Stéphane Mallat. Sparse Geometric Image Representations With Bandelets. IEEE Transactions in Image Processing, 14(4):423, 2005 abstract.
  • Benjamin T Vincent, Roland J Baddeley, Tom Troscianko, Iain D Gilchrist. Is the early visual system optimised to be energy efficient?. Network: Computation in Neural Systems, 16(2-3):175--90, 2005 abstract.
  • Evan C. Smith, Michael S. Lewicki. Efficient Auditory Coding, URL . Nature, 439(7079):978--82, 2006 abstract.
  • Paul A. Watters. Are sparse-coding simple cell receptive field models physiologically plausible?, URL URL2 . Journal of Integrative Neuroscience, 5(3):333--53, 2006 abstract.
  • Laurent U. Perrinet. An efficiency razor for model selection and adaptation in the primary visual cortex, URL URL2 . In Fifteenth Annual Computational Neuroscience Meeting, 2006 abstract.
  • Martin Rehn, Friedrich T. Sommer. Storing and restoring visual input with collaborative rank coding and associative memory. Neurocomputing, 69:1219---23, 2006 abstract.
  • Bruno Cessac, Manuel Samuelides. From neuron to neural networks dynamics, URL URL2 . pages 7--88. abstract.
  • Laurent U. Perrinet. Neural Codes for Adaptive Sparse Representations of Natural Images, URL URL2 . In Mathematical image processing meeting (Marseille, France) September 5, 2007, 2007 abstract.
  • Martin Rehn, Friedrich T. Sommer. A model that uses few active neurones to code visual input predicts the diverse shapes of cortical receptive fields. Journal of Computational Neuroscience, 22(2):135--46, 2007 abstract.
  • Laurent U. Perrinet. Dynamical Neural Networks: modeling low-level vision at short latencies, URL URL2 URL3 . pages 163--225. abstract.
  • Marc' Aurelio Ranzato, Christopher S. Poultney, Sumi Chopra, Yan LeCun. Efficient Learning of Sparse Overcomplete Representations with an Energy-Based Model. pages 1137--44. abstract.
  • Thomas Blumensath, Mike E. Davies. Iterative Thresholding for Sparse Approximations. The Journal of Fourier Analysis and Applications, 2007 abstract.
  • Thomas Blumensath, Michael E. Davies. Rate-Distortion Analysis of Sparse Overcomplete Codes. 2007 abstract.
  • Eizaburo Doi, Doru C. Balcan, Michael S. Lewicki. Robust Coding over Noisy Overcomplete Channels., URL URL2 . IEEE Transactions in Image Processing, 16(2):442--52, 2007 abstract.
  • Honglak Lee, Alexis Battle, Rajat Raina, Andrew Ng. Efficient sparse coding algorithms. In Advances in Neural Information Processing Systems 19, pages 801--808. MIT Press, Cambridge, MA, 2007 abstract.
  • Laurent U. Perrinet. On efficient sparse spike coding schemes for learning natural scenes in the primary visual cortex, URL URL2 URL3 URL4 . In Sixteenth Annual Computational Neuroscience Meeting: CNS*2007, Toronto, Canada. 7--12 July 2007, 2007 abstract.
  • Christopher J. Rozell, Don H. Johnson, Richard G. Baraniuk, Bruno A. Olshausen. Sparse coding via thresholding and local competition in neural circuits, URL . Neural Computation, 20(10):2526--63, 2008 abstract.
  • Cornelius Weber, Jochen Triesch. A sparse generative model of V1 simple cells with intrinsic plasticity, URL URL2 . Neural Computation, 20(5):1261--84, 2008 abstract.
  • Laurent U. Perrinet. What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells, URL URL2 . In Proceedings of COSYNE, 2008, 2008 abstract.
  • Laurent U. Perrinet. Role of homeostasis in learning sparse representations, URL URL2 URL3 URL4 URL5 . Neural Computation, 22(7):1812--36, 2010 abstract.

related bibliography on vision

  • Geoffrey H. Henry, P. O. Bishop, B. Dreher. Orientation, axis and direction as stimulus parameters for striate cells.. Vision Research, 14:767--77, 1974 abstract.
  • Geoffrey H. Henry, B. Dreher, P. O. Bishop. Orientation specificity of cells in cat striate cortex.. Journal of Neurophysiology, 37:1394--409, 1974 abstract.
  • David Marr. Analyzing Natural Images: A Computational Theory of Texture Vision. Technical report, Massachusetts Institute of Technology, Artificial Intelligence Laboratory, 1975.
  • Charles D. Gilbert, T. N. Wiesel. Morphology and intracortical projections of functionally characterised neurones in the cat visual cortex.. Nature, 280(5718):120--5, 1979 abstract.
  • David Marr. Vision. W. H. Freeman and Company, NY, 1982.
  • I. Biederman. Human Image Understanding: Recent Research and a Theory. Computer Graphics, Vision and Image Processing, 32:29-73, 1985 abstract.
  • G. Sclar, J.H.R. Maunsell, P. Lennie. Coding of image contrast in central visual pathways of the macaque monkey. Vision Research, 30:1--10, 1990 abstract.
  • Pierre Buser, Michel Imbert. Vision. A Bradford Book, 1992.
  • Charles D. Gilbert. Adult Cortical Dynamics, URL . Physiological Review, 78(2):467-485, 1998 abstract.
  • M.P. Sceniak, Dario L. Ringach, M.J. Hawken, S. Shapley. Contrast's effect on spatial summation by macaque V1 neurons. Nature Neuroscience, 2:753--9, 1999 abstract.
  • K. Kawano. Ocular tracking: behavior and neurophysiology. Current Opinion in Neurobiology, 9:467--73, 1999 abstract.
  • J Xing, D J Heeger. Center-surround interactions in foveal and peripheral vision, URL . Vision Research, 40(22):3065--72, 2000 abstract.
  • James R. Cavanaugh, Wyeth Bair, J. Anthony Movshon. Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons, URL . Journal of Neurophysiology, 88(5):2530--46, 2002 abstract.
  • Karl R Gegenfurtner. Cortical mechanisms of colour vision., URL . Nature Reviews Neuroscience, 4(7):563-72, 2003 abstract.
  • Bruno A. Olshausen. What is the other 85\% of V1 doing?. In Problems in Systems Neuroscience, Oxford University Press, 2004 abstract.
  • Benjamin T Vincent, Roland J Baddeley, Tom Troscianko, Iain D Gilchrist. Is the early visual system optimised to be energy efficient?. Network: Computation in Neural Systems, 16(2-3):175--90, 2005 abstract.
  • Laurent U. Perrinet, Jens Kremkow. Dynamical contrast gain control mechanisms in a layer 2/3 model of the primary visual cortex. In Physiogenic and pathogenic oscillations: the beauty and the beast, 5th INMED/TINS CONFERENCE SEPTEMBER 9 - 12, 2006, La Ciotat, France, 2006 abstract.
  • B.M. Sheliga, E.J. FitzGibbon, Fred A. Miles. Spatial summation properties of the human ocular following response (OFR): evidence for nonlinearities due to local ang global inhibitory interactions. Vision Research, 48:1758-1776, 2008 abstract.

related bibliography on Bayes and the Ideal Observer

  • W. S. Albrecht, D. G. Geisler. Bayesian Analysis of Identification Performance in Monkev Visual Cortex: Nonlinear Mechanisms and Stimulus Certainty. Vision Research, 35(19):2723--30, 1995 abstract.
  • Thomas Bayes. An Essay Toward Solving a Problem in the Doctrine of Chances. Philosophical Transactions of the Royal Society of London, 53:370--418, 1764 abstract.
  • Francis Colas. Perception des objets en mouvement Composition bayésienne du flux optique et du mouvement de l'observateur. 2006 abstract.
  • Wilson S. Geisler, Duane G. Albrecht, Alison M. Crane. Responses of neurons in primary visual cortex to transient changes in local contrast and luminance., URL URL2 . Journal of Neuroscience, 27(19):5063--7, 2007 abstract.
  • Wilson S. Geisler, Duane G. Albrecht. Visual cortex neurons in monkeys and cats: Detection, discrimination, and identification. Visual Neuroscience, 1(14):897--919, 1997 abstract.
  • Felix Hurlimann, Daniel C Kiper, Matteo Carandini. Testing the Bayesian model of perceived speed. Vision Research, 42(19):2253--7, 2002 abstract.
  • D. Kersten, Pascal Mamassian, Alan L. Yuille. Object perception as Bayesian inference. Annual Review of Psychology, 55, 2003 abstract.
  • E. Koechlin, J.L. Anton, Y. Burnod. Bayesian inference in populations of cortical neurons: A model of motion integration and segmentation in area MT. Biological Cybernetics, 80:25--44, 1999 abstract.
  • Tai Sing Lee, David Mumford. Hierarchical Bayesian Inference in the Visual Cortex. Journal of Optical Society of America, A., 20(7):1434-1448, 2003 abstract.
  • Wei Ji Ma, Jeffrey M. Beck, Peter E. Latham, Alexandre Pouget. Bayesian inference with probabilistic population codes. Nature Neuroscience, 2006 abstract.
  • Pascal Mamassian. Bayesian modelling of visual perception. pages 13--36. abstract.
  • Anna Montagnini, Pascal Mamassian, Laurent Perrinet, Eric Castet, Guillaume S. Masson. Bayesian modeling of dynamic motion integration. In 1ère conférence francophone NEUROsciences COMPutationnelles (NeuroComp), 2006 abstract.
  • Anna Montagnini, Pascal Mamassian, Laurent Perrinet, Eric Castet, Guillaume S. Masson. Bayesian modeling of dynamic motion integration, URL URL2 . Journal of Physiology (Paris), 101(1-3):64-77, 2007 abstract.
  • Anna Montagnini, Pascal Mamassian, Laurent Perrinet, Eric Castet, Guillaume S. Masson. Dynamic inference for motion tracking, URL URL2 . In Perception 36 ECVP Abstract Supplement, 2007 abstract.
  • Anna Montagnini, Pascal Mamassian, Laurent Perrinet, Guillaume S. Masson. Visual tracking of ambiguous moving objects: A recursive Bayesian model, URL URL2 URL3 . Journal of Vision, 7(9):406, 2007 abstract.
  • Laurent Perrinet, Frédéric Barthélemy, Eric Castet, Guillaume S. Masson. Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model. In Perception, pages 38. 2005 abstract.
  • Eero P. Simoncelli. Bayesian Multi-scale Differential Optical Flow, URL URL2 . In Handbook of Computer Vision and Applications, pages 397--422. Academic Press, San Diego, 1999 abstract.
  • Yair Weiss, Edward H. Adelson. Slow and smooth: a Bayesian theory for the vision combination of local motion signals in human, URL URL2 . Technical report, MIT, 1998.

related bibliography - information theory + efficient coding

  • Horace B. Barlow. Redundancy reduction revisited. Network: Computation in Neural Systems, 12:241---25, 2001 abstract.
  • J M Beck, Alexandre Pouget. Exact inferences in a neural implementation of a hidden Markov model, URL URL2 URL3 URL4 . Neural Computation, 19(5):1344-1361, 2007 abstract.
  • Michael J. Black, David J. Fleet. Probabilistic Detection and Tracking of Motion Boundaries, URL URL2 . International Journal of Computer Vision, 38(3):231--245, 2000 abstract.
  • Pierre-Yves Burgi, Alan L. Yuille, Norberto M Grzywacz. Probabilistic motion estimation based on temporal coherence, URL . Neural Computation, 12(8):1839--67, 2000 abstract.
  • Gustavo Deco, Dragan Obradovic. An information-theoretic approach to neural computing. Springer Verlag, 1996.
  • Sophie Denève, J R Duhamel, Alexandre Pouget. Optimal sensorimotor integration in recurrent cortical networks: a neural implementation of Kalman filters, URL URL2 URL3 . Journal of Neuroscience, 27(21):5744-5756, 2007 abstract.
  • David J. Field. Relations between the statistics of natural images and the response properties of cortical cells. Optical Society of America A, 4(12):2379--94, 1987 abstract.
  • David J. Field. What is the goal of sensory coding?, URL . Neural Computation, 6(4):559--601, 1994 abstract.
  • Felix Hurlimann, Daniel C Kiper, Matteo Carandini. Testing the Bayesian model of perceived speed. Vision Research, 42(19):2253--7, 2002 abstract.
  • Mehrdad Jazayeri, J. Anthony Movshon. Optimal representation of sensory information by neural populations. Nature Neuroscience, 2006 abstract.
  • Mehrdad Jazayeri, J. Anthony Movshon. A new perceptual illusion reveals mechanisms of sensory decoding. Nature, 446:912--5, 2007 abstract.
  • Vera Kurkova. Kolmogorov's Theorem. pages 501--2. abstract.
  • K Langley, S J Anderson. Subtractive and divisive adaptation in visual motion computations, URL URL2 URL3 URL4 URL5 . Vision Research, 47(5):673-686, 2007 abstract.
  • Bruno A. Olshausen, David J. Field. Natural image statistics and efficient coding. Network: Computation in Neural Systems, 7:333--9, 1996 abstract.
  • Laurent Perrinet, Frédéric Barthélemy, Eric Castet, Guillaume S. Masson. Dynamics of motion representation in short-latency ocular following: A two-pathways Bayesian model. In Perception, pages 38. 2005 abstract.
  • Laurent Perrinet, Guillaume S. Masson. Modeling spatial integration in the ocular following response using a probabilistic framework, URL URL2 . Journal of Physiology (Paris), 101(1--3):46--55, 2007 abstract.
  • X. Pitkow, Haim Sompolinsky, Markus Meister. A Neural Computation for Visual Acuity in the Presence of Eye Movements, URL . PLoS Biology, 5(12):e331, 2007 abstract.
  • Claude E. Shannon. A Mathematical Theory of Communication. Bell System Technical Journal, 27:379-423, 623-56, 1948 abstract.
  • Claude Elwood Shannon, Warren Weaver. The mathematical theory of communication. The University of Illinois Press, Urbana, 1964.
  • Benjamin T Vincent, Roland J Baddeley, Tom Troscianko, Iain D Gilchrist. Is the early visual system optimised to be energy efficient?. Network: Computation in Neural Systems, 16(2-3):175--90, 2005 abstract.
  • Yair Weiss, Eero P. Simoncelli, Edward H Adelson. Motion illusions as optimal percepts, URL URL2 . Nature Neuroscience, 5(6):598--604, 2002 abstract.
  • Yair Weiss. Bayesian motion estimation and segmentation, URL URL2 . (1624), 1998 abstract.
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