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Oren Kolodny, Shimon Edelman, and Arnon Lotem, Evolution of continuous learning of the structure of the environment, Journal of the Royal Society Interface 11:20131091 (2014).
Shimon Edelman, How to write a "How to Build a Brain" book (a review of How to Build a Brain, C. Eliasmith, Oxford University Press, 2013), Trends in Cognitive Sciences 18:118-119 (2014). [This is a preprint of an article whose final and definitive text, published in TiCS, may differ.]


Oren Kolodny, Arnon Lotem, and Shimon Edelman, Learning a generative probabilistic grammar of experience: a process-level model of language acquisition, Cognitive Science, in press.
complex networks for fMRI
Tomer Fekete, Meital Wilf, Denis Rubin, Shimon Edelman, Rafael Malach, and Lilianne R. Mujica-Parodi, Combining classification with fMRI-derived complex network measures for potential neurodiagnostics, PLoS ONE 8(5): e62867 (2013).


new Chorus
Shimon Edelman and Reza Shahbazi, Renewing the Respect for Similarity, Frontiers in Computational Neuroscience (part of a Frontiers Research Topic, Invariant Recognition of Visual Objects), 6:45 (2012).
30 Marr
Shimon Edelman, Vision, reanimated and reimagined, (special issue on the 30th anniversary of the publication of Marr's Vision), Perception, 41:1116-1127 (2012).
six challenges
Shimon Edelman, Six challenges to theoretical and philosophical psychology, an inaugural editorial for Frontiers in Theoretical and Philosophical Psychology 3:219 (2012).
Yue Gao, Eyal Nitzany, and Shimon Edelman, Online learning of causal structure in a dynamic game situation, Proc. 34th Cognitive Science Society Conference, Sapporo, Japan, July 2012, pages 372-377.


Luca Onnis, Shimon Edelman, and Heidi Waterfall, Local statistical learning under cross-situational uncertainty, Proc. 33rd Cognitive Science Society Conference, Boston, MA, July 2011.
Reza Shahbazi, David J. Field, and Shimon Edelman, The role of hierarchy in learning to categorize images, Proc. 33rd Cognitive Science Society Conference, Boston, MA, July 2011.
being in time
Shimon Edelman and Tomer Fekete, Being in Time, extended abstract for the poster presented at the 15th meeting of the Association for Scientific Study of Consciousness (ASSC15), June 2011, Kyoto, Japan.
dreaming and reality (or, the truth about Inception)
Shimon Edelman, Regarding Reality: Some Consequences of Two Incapacities, Frontiers in Theoretical and Philosophical Psychology, 2011.
computational phenomenology
Tomer Fekete and Shimon Edelman, Towards a computational theory of experience, Consciousness and Cognition, 20:807-827 (2011). Final draft.
Shimon Edelman, On look-ahead in language: navigating a multitude of familiar paths, in Predictions in the Brain, M. Bar, ed. (Oxford University Press, March 2011). Penultimate draft.
in defence of metaphysics
Shimon Edelman, The metaphysics of embodiment (part of a collective review of Embodiment and the Inner Life — Cognition and Consciousness in the Space of Possible Minds by M. Shanahan, Oxford University Press, 2010, International Journal of Machine Consciousness 3:321-325, 2011).
Catherine L. Caldwell-Harris, Jonathan Berant, and Shimon Edelman, Measuring mental entrenchment of phrases with perceptual identification, familiarity ratings, and corpus frequency statistics, to appear in S. T. Gries and D. Divjak (eds.), Frequency effects in cognitive linguistics (Vol. 1): Statistical effects in learnability, processing and change, The Hague, The Netherlands: De Gruyter Mouton (2011).


Michael H. Goldstein, Heidi R. Waterfall, Arnon Lotem, Joseph Halpern, Jennifer Schwade, Luca Onnis, and Shimon Edelman, General cognitive principles for learning structure in time and space, Trends in Cognitive Sciences 14:249-258 (2010).
Heidi R. Waterfall, Ben Sandbank, Luca Onnis, and Shimon Edelman, An empirical generative framework for computational modeling of language acquisition, Journal of Child Language 37:671-703 (2010).
DIRain dynamics
Evan Balaban, Shimon Edelman, Sten Grillner, Uri Grodzinski, Erich D. Jarvis, Jon H. Kaas, Gilles Laurent, and Gordon Pipa, Evolution of Dynamic Coordination, in Dynamic Coordination in the Brain: From Neurons to Mind, edited by C. von der Malsburg, W. A. Phillips, and W. Singer. Strüngmann Forum Report, vol. 5 (MIT Press, 2010).


Shimon Edelman and Zach Solan, Machine Translation Using Automatically Inferred Construction-based Correspondence and Language Models, Proc. 23rd Pacific Asia Conference on Language, Information, and Computation (PACLIC-23), Hong Kong, December 2009. [The pseudocode accompanying that paper is here] [If you happen to have been one of the reviewers of this paper for PACLIC, please read this].
Heidi Waterfall and Shimon Edelman, The Neglected Universals: Learnability Constraints and Discourse Cues, a commentary on The myth of language universals: Language diversity and its importance for cognitive science by Evans and Levinson, Behavioral and Brain Sciences 32:471-472 (2009).
Shimon Edelman, On what it means to see, and what we can do about it, in Object Categorization: Computer and Human Vision Perspectives, S. Dickinson, A. Leonardis, B. Schiele, and M. J. Tarr, eds., chapter 4, pp. 69-86 (Cambridge University Press, 2009). Penultimate draft.


Luca Onnis, Heidi Waterfall, and Shimon Edelman, Learn Locally, Act Globally: Learning Language from Variation Set Cues, Cognition 109:423-430 (2008).
Martin Giese, Ian Thornton, and Shimon Edelman, Metrics of the perception of body movement, Journal of Vision 8:9:13 (2008).
Shimon Edelman, On the Nature of Minds, or: Truth and Consequences; this is a preprint of an article whose final and definitive form has been published in a special issue of the Journal of Experimental and Theoretical AI (JETAI), 20:181-196 © 2008 Taylor & Francis (with commentaries by Van Orden, Spivey & Anderson, Dietrich, and Markman). JETAI is available online at
Shimon Edelman, A swan, a pike, and a crawfish walk into a bar, Edelman's response to the commentaries on Truth and Consequences, JETAI 20:261-268, 2008 (see above).
Guy Tannenbaum, Yehezkel Yeshurun, and Shimon Edelman, Trade-off Between Capacity and Generalization in a Model of Memory, Proc. 30th Cognitive Science Society Conference, Washington, DC, July 2008.
Jonathan Berant, Catherine Caldwell-Harris, and Shimon Edelman, Tracks in the Mind: Differential Entrenchment of Common and Rare Liturgical and Everyday Multiword Phrases in Religious and Secular Hebrew Speakers, Proc. 30th Cognitive Science Society Conference, Washington, DC, July 2008.
Luca Onnis, Heidi Waterfall, and Shimon Edelman, Variation Sets Facilitate Artificial Language Learning, Proc. 30th Cognitive Science Society Conference, Washington, DC, July 2008.


Shimon Edelman and Heidi Waterfall, Behavioral and computational aspects of language and its acquisition, Physics of Life Reviews 4:253-277 (2007) [see the abstract].
Peter Brodsky, Heidi Waterfall, and Shimon Edelman, Characterizing Motherese: on the computational structure of child-directed language, in Proc. Cognitive Science Society Conference (2007).
Jonathan Berant, Yaron Gross, Matan Mussel, Ben Sandbank, Eytan Ruppin, and Shimon Edelman, Boosting unsupervised grammar induction by splitting complex sentences on function words, in Proc. of the 31st Boston University Conference on Language Development (Cascadilla Press, 2007).
Shimon Edelman, Bridging language with the rest of cognition: computational, algorithmic and neurobiological issues and methods, in the Proceedings of the Ithaca EMCL workshop (John Benjamins, 2007).


On Noë
Shimon Edelman, Mostly Harmless (review of Action in Perception by Alva Noë, MIT Press, 2005); Artificial Life 12:183-186 (2006).


Zach Solan, David Horn, Eytan Ruppin, and Shimon Edelman, Unsupervised learning of natural languages, in Proc. Natl. Acad. Sci. 102:11629-11634 (August 16, 2005) [see the abstract and the supplementary material].
Vered Kunik, Zach Solan, Shimon Edelman, Eytan Ruppin and David Horn, Motif Extraction and Protein Classification, presented at CSB, August 2005.
Fiona N. Newell, Dianne M. Sheppard, Shimon Edelman, and Kimron L. Shapiro, The interaction of shape- and location-based priming in object categorisation: Evidence for a hybrid "what+where" representation stage, Vision Research 45:2065-2080 (2005).
Shimon Edelman, Zach Solan, Eytan Ruppin and David Horn, Learning syntactic constructions from raw corpora, in Proc. of the 29th Boston University Conference on Language Development (Cascadilla Press, 2005).


statistical learning in vision
Shimon Edelman and Nathan Intrator, Unsupervised statistical learning in vision: computational principles, biological evidence, extended abstract of invited talk at the ECCV-2004 Workshop on Statistical Learning in Computer Vision, Prague, May 2004.
Bo Pedersen, Shimon Edelman, Zach Solan, David Horn, and Eytan Ruppin, Some Tests of an Unsupervised Model of Language Acquisition, in Proc. COLING-2004 Workshop on Psycho-computational Models of Human Language Acquisition, (Geneva, Switzerland, August 2004)
Shimon Edelman, Zach Solan, David Horn and Eytan Ruppin, Bridging computational, formal and psycholinguistic approaches to language, in Proc. of the 26th Conference of the Cognitive Science Society (Chicago, IL, August 2004), Ken Forbus, Dedre Gentner, and Terry Regier, eds.
on Briscoe
Shimon Edelman and Bo Pedersen, review of Linguistic Evolution through Language Acquisition (Ted Briscoe, ed., Cambridge University Press, 2002), Journal of Linguistics vol. 40(2):14-18, 2004.
Zach Solan, David Horn, Eytan Ruppin, and Shimon Edelman, Unsupervised context sensitive language acquisition from a large corpus, in Proc. 2003 Conf. on Neural Information Processing Systems (NIPS), L. Saul, ed., MIT Press, 2004 (not the final version!); [see abstract].
Zach Solan, David Horn, Eytan Ruppin, and Shimon Edelman, Evolution of language diversity: why fitness counts, in Proc. 4th International Conference on Language Evolution, M. Tallerman, ed., Oxford University Press (to appear) [not the final version!] [see abstract].
on Jackendoff
Shimon Edelman, Generative grammar with a human face? (a commentary on Foundations of language, R. Jackendoff, (Oxford University Press, 2003), Behavioral and Brain Sciences).


representations and dynamical systems
Shimon Edelman, But will it scale up? Not without representations (a commentary on The dynamics of active categorical perception in an evolved model agent by R. Beer), Adaptive Behavior 11:273-275, 2003.
Shimon Edelman, Zach Solan, David Horn and Eytan Ruppin, Rich Syntax from a Raw Corpus: Unsupervised Does It, position paper presented at Syntax, Semantics and Statistics — a NIPS'03 workshop (Whistler, BC, Dec. 2003) [abstract].
nature of language
Shimon Edelman, A New Vision of Language:
learning language
Zach Solan, Eytan Ruppin, David Horn and Shimon Edelman, Unsupervised Efficient Learning and Representation of Language Structure, Proc. of the 25th Conference of the Cognitive Science Society (Boston, MA, July 2003), R. Alterman and D. Kirsh, eds.
Shimon Edelman and Morten H. Christiansen, How seriously should we take Minimalist syntax? A comment on Lasnik, Trends in Cognitive Sciences, 7:59-60, February 2003.
bio-motion (ECVP abstract)
Ian M. Thornton, Martin A. Giese and Shimon Edelman, Representing biological motion, Proc. ECVP'03, Perception, September 2003.
bio-motion (VSS abstract)
Martin A. Giese, Ian M. Thornton and Shimon Edelman, Metric category spaces of biological motion, Proc. VSS'03, Journal of Vision, May 2003.
visual systematicity
Shimon Edelman and Nathan Intrator, Towards structural systematicity in distributed, statically bound visual representations, Cognitive Science, 27:73-110 (2003) [see abstract, and also our response to John Hummel's comments on this article, both published in Cognitive Science].


final frontier
Shimon Edelman, Multidimensional space: the final frontier, Nature Neuroscience 5:1252-1254, 2002 (News and Views feature). [Note: the Nature proofreader changed the original "challenge" to "challange" in two places in this paper; in the version available here, I corrected this error].
linguistic structure
Zach Solan, Eytan Ruppin, David Horn and Shimon Edelman, Automatic acquisition and efficient representation of syntactic structures, in Proc. 2002 Conf. on Neural Information Processing Systems (NIPS), S. Thrun, ed., MIT Press, 2003 [see abstract].
visual structure
Shimon Edelman, Nathan Intrator and Judah S. Jacobson, Unsupervised learning of visual structure, Lecture Notes in Computer Science, vol. 2025, H. H. Bülthoff, T. Poggio, S. W. Lee and C. Wallraven, eds., 629-643, Springer, 2002 [see abstract].
Shimon Edelman, Constraining the neural representation of the visual world, Trends in Cognitive Sciences 6:125-131, 2002 [see abstract].
perceptual learning
Edelman, S., and N. Intrator, Models of perceptual learning, in Perceptual learning, M. Fahle and T. Poggio, eds., MIT Press, 2002.


Shimon Edelman, Benjamin P. Hiles, Hwajin Yang and Nathan Intrator, Probabilistic principles in unsupervised learning of visual structure: human data and a model (not the final version!), in Proc. 2001 Conf. on Neural Information Processing Systems (NIPS), S. Becker, ed., MIT Press, 2002 [see abstract].
translation (non)invariance
Dill, M., and S. Edelman, Imperfect invariance to object translation in the discrimination of complex shapes, Perception, 30:707-724 (2001) [see abstract]
Shimon Edelman and Nathan Intrator, Visual Processing of Object Structure, in The Handbook of Brain Theory and Neural Networks (2nd ed.), M. A. Arbib, ed., MIT Press, 2002.
neural spaces
S. Edelman, Neural spaces: a general framework for the understanding of cognition?, a commentary on Roger Shepard's BBS article, Perceptual-Cognitive Universals as Reflections of the World, Behavioral and Brain Sciences, 24 (2001).
face views
S. Edelman, and A. O'Toole, Viewpoint generalization in face recognition: The role of category-specific processes, in Computational, geometric, and process perspectives on facial cognition: Contexts and challenges, M. Wenger and J. Townsend, eds., Erlbaum (2001).


Shimon Edelman and Nathan Intrator, A productive, systematic framework for the representation of visual structure, in Proc. 2000 Conf. on Neural Information Processing Systems (NIPS), 10-16, T. Leen, ed., MIT Press, 2001 [see abstract].
David Marr's bio
S. Edelman and L. M. Vaina, David Marr (a short biography), International Encyclopaedia of Social and Behavioral Sciences, Pergamon, 2001.
S. Edelman and N. Intrator, (Coarse Coding of Shape Fragments) + (Retinotopy) = Representation of Structure, Proc. Intl. Workshop on Object Recognition (OR'99), Bad Homburg, May 1999, Spatial Vision, 13:255-264, 2000 [see abstract].


Teichmuller spaces for shape representation   (this is Appendix C of my book, Representation and Recognition in Vision, MIT Press, May 1999)
Review of Neural Organization (M. A. Arbib, P. Erdi and J. Szentagothai, MIT Press, 1998)
Duvdevani-Bar, S., and S. Edelman, Visual recognition and categorization on the basis of similarities to multiple class prototypes, Intl. J. of Computer Vision, 33:201-228 (1999) [see abstract]
on impenetrability
S. Edelman, No reconstruction, no impenetrability (at least not much), a commentary on Pylyshyn's BBS article, Is vision continuous with cognition?, Behavioral and Brain Sciences 22:376 (1999).
all the way
S. Edelman and E. M. Breen, On the virtues of going all the way, a commentary on Barsalou's BBS article, Perceptual Symbol Systems, Behavioral and Brain Sciences, 22:614 (1999).


fMRI / shape space
S. Edelman, K. Grill-Spector, T. Kushnir, and R. Malach, Towards direct visualization of the internal shape representation space by fMRI, Psychobiology (special issue on Cognitive Neuroscience of Object Representation and Recognition), 26, 309-321, 1998 [see abstract].
face space
S. Edelman, Spanning the face space, Journal of Biological Systems, 6, 265-280, 1998 [see abstract]
S. Edelman and F. N. Newell, Iconic representation of object structure: evidence from differential priming of shape and location, Sussex University COGS CSRP 500, November 1998 [see abstract]
Edelman, S., Representation is Representation of Similarities, Behavioral and Brain Sciences 21:449-498, 1998 [see abstract; the RESPONSE to the commentaries is here.]
Cutzu, F., and S. Edelman, Representation of object similarity in human vision: psychophysics and a computational model, Vision Research 38:2227-2257, 1998 [see abstract. A short version of this paper (in Proc. Natl. Acad. Sci., 1996) is also available.]


Edelman, S., and S. Duvdevani-Bar, Similarity-based viewspace interpolation and the categorization of 3D objects, in Proc. Edinburgh Workshop on Similarity and Categorization, 75-81, November 1997. [see abstract]
theories of recognition
Edelman, S., Computational theories of object recognition, Trends in Cognitive Sciences, 1:296-304, 1997 [see abstract]
complex cells
Edelman, S., N. Intrator, and T. Poggio, Complex cells and object recognition, unpublished manuscript [see abstract]
Edelman, S., and S. Duvdevani-Bar, A model of visual recognition and categorization, Phil. Trans. Royal Soc. (B), 352:1191-1202 (1997).
Edelman, S., and N. Intrator, Learning as extraction of low-dimensional representations, in Mechanisms of Perceptual Learning, D. Medin, R. Goldstone, and P. Schyns, eds., (Psychology of Learning and Motivation series), Academic Press, 1997 [see abstract].
Intrator, N., and S. Edelman, Learning low dimensional representations of visual objects with extensive use of prior knowledge, Network, 8:259-281, 1997. [see abstract].


Edelman, S., H. H. Bülthoff, and I. Bülthoff, Effects of parametric manipulation of inter-stimulus similarity on 3D object recognition, Spatial Vision, 12:107-123, 1999 [see abstract].
Edelman, S., and S. Duvdevani-Bar, Similarity, connectionism, and the problem of representation in vision, Neural Computation 9:701-720 (1997) [see abstract].
Edelman, S., F. Cutzu, and S. Duvdevani-Bar, Similarity to reference shapes as a basis for shape representation, in Proc. COGSCI'96, [see abstract].
Karov, Y., and S. Edelman, Similarity-based word sense disambiguation, Computational Linguistics, 1998, 24: 41-59 [see abstract]


Edelman, S., Vision Reanimated, unpublished manuscript [see abstract].
Edelman, S., Receptive Fields for Vision: from Hyperacuity to Object Recognition, Weizmann Institute CS-TR 95-29, 1995 [see abstract].
Intrator, N., and S. Edelman, How to make a low-dimensional representation suitable for diverse tasks, Connection Science, 1996 [see abstract].
Intrator N., S. Edelman and H. H. Bülthoff, An integrated approach to the study of object features in visual recognition, Network 6:603-618, 1995.
Edelman, S., How representation works is more important than what representations are, A commentary on D. Amit, "The Hebbian paradigm reintegrated: Local reverberations as internal representations", Behavioral and Brain Sciences, 18:630-631, December 1995. [see abstract]
Cutzu, F., and S. Edelman, Explorations of shape space, Weizmann Institute CS-TR 95-01, 1995; a shorter version (Proc. Natl. Acad. Sci., 93:12046-12050, 1996) is here [see abstract].
Grill Spector, K., S. Edelman, and R. Malach, Anatomical origin and computational role of diversity in the response properties of cortical neurons in Proc. 1994 Conf. on Neural Information Processing Systems (NIPS-7), 117-124, G. Tesauro, D. Touretzky, J. Alspector, eds., Morgan Kauffman, 1995 [see abstract].
Edelman, S., Representation of similarity in 3D object discrimination, Weizmann Institute CS-TR 94-02, 1994, also Neural Computation 7:407-422, 1995. [see abstract].
Lando, M., and S. Edelman, Generalization from a single view in face recognition, Weizmann Institute CS-TR 95-02, 1995; also published in Network 6:551-576, 1995. [see abstract]. A short 6-page version of this TR, presented at IWAFGR'95, is also available. Note.
Edelman, S., Class similarity and viewpoint invariance in the recognition of 3D objects, Biol. Cybern., 72:207-220 (1995); [see abstract].
Duvdevani-Bar, S., and S. Edelman, On similarity to prototypes in 3D object representation, Weizmann Institute CS-TR 95-11, 1995 [see abstract].
Edelman, S., and Y. Weiss, Vision: Hyperacuity, in The Handbook of Brain Theory and Neural Networks, M. A. Arbib, ed., 1009-1011, MIT Press, 1995.


Jungman, N., A. Levi, A. Aperman, and S. Edelman, Automatic classification of police mugshot album using principal component analysis, Proc.\SPIE-2243 (Conference on Applications of Artificial Neural Networks), 591-594, S. K. Rogers and D. W. Ruck, eds., Orlando, FL, March 1994.
Edelman, S., Representation, Similarity and the Chorus of Prototypes, Weizmann Institute CS-TR 93-10, 1993 (revised June 1994); Minds and Machines, 5:45-68, 1995 [see abstract].
Edelman, S., and D. Weinshall, Computational approaches to object constancy, in Perceptual constancies, V. Walsh and J. Kulikowski, eds., Cambridge U. Press (1994) [see abstract].
Cutzu, F., and S. Edelman, Viewpoint-dependence of response time in object recognition, Vision Research, 34:3037-3056, 1994 [see abstract]
Edelman, S., Representation without Reconstruction, CVGIP:IU, 60:92-94, 1994. [see abstract].
Weiss, Y., and S. Edelman, Representation with receptive fields: gearing up for recognition, Weizmann Institute CS-TR 93-09, 1993 (revised January 1994). A revised version published as Representation of similarity as a goal of early visual processing, Network, 6:19-42, 1995 [see abstract].
Kamon, I., T. Flash, and S. Edelman, Learning to grasp using visual information, Weizmann Institute CS-TR 94-04, 1994 (a revised version, published in IEEE Transactions on Systems, Man, and Cybernetics 28:266-276, 1998, is here).
Hel-Or, Y., and S. Edelman, A new approach to qualitative stereo, Proc. ICPR'94, Jerusalem, 316-320, 1994. [see abstract].
Edelman, S., Biological Constraints and the Representation of Structure in Vision and Language, Psycoloquy, 5:57, Sept. 25, 1994. [see abstract].


Edelman, S., The Illusion of Reality (a multiple book review), Mathematical Intelligencer 15(4):68-70 (1993).
Weiss, Y., S. Edelman, and M. Fahle, Models of perceptual learning in vernier hyperacuity, Neural Computation 5:695-718, 1993. [see abstract].
Manolache, F., and S. Edelman, Generation of natural-looking 3D shapes by simulated evolution, Weizmann Institute CS-TR 93-13, 1993.
Moses, Y., S. Ullman, and S. Edelman, Generalization across changes in illumination and viewing position in upright and inverted faces, Weizmann Institute CS-TR 93-14, 1993; also Perception, 1996. [see abstract].
Edelman, S., On learning to recognize 3D objects from examples, IEEE Trans. PAMI 15:833-837, 1993.
Edelman, S., Representing 3D objects by sets of activities of receptive fields, Biological Cybernetics, 70:37-45, 1993. [see abstract].


Poggio, T., M. Fahle, and S. Edelman, Fast Perceptual Learning in Visual Hyperacuity, Science, New Series, 256:1018-1021 (1992).
H. H. Bülthoff and S. Edelman, Psychophysical support for a 2D view interpolation theory of object recognition, PNAS 89:60-64, 1992. [see abstract].
Edelman, S., D. Reisfeld and Y. Yeshurun, Learning to recognize faces from examples, Proc. 2nd European Conf. on Computer Vision, Lecture Notes in Computer Science 588:787-791, Springer, 1992.
Poggio, T., S. Edelman and M. Fahle, Learning of visual modules from examples: a framework for understanding adaptive visual performance, Computer Vision, Graphics and Image Processing: Image Understanding 56:22-30, 1992.
Edelman, S., Visual Perception, in the Encyclopedia of Artificial Intelligence, 2:1655-1663, S. Shapiro, ed., Wiley, 1992.
Edelman, S., and H. H. Bülthoff, Modeling human visual object recognition, Proc. Intl. Joint Conf. on Neural Networks IV:37-42, 1992.
Edelman, S., and T. Poggio, Bringing the Grandmother back into the picture: a memory-based view of object recognition, Intl. J. of Pattern Recognition and Artificial Intelligence 6:37-62, 1992.
Edelman, S., and H. H. Bülthoff, Orientation dependence in the recognition of familiar and novel views of 3D objects, Vision Research 32:2385-2400, 1992. [see abstract].
Intrator, N., J. I. Gold, H. H. Bülthoff and S. Edelman, 3D object recognition using unsupervised feature extraction, in Proc. 1991 Conf. on Neural Information Processing Systems (NIPS), D. Tourezky, ed., Morgan Kauffman, 1992.

1991 and earlier

Edelman, S., and H. H. Bülthoff, Viewpoint-specific representations in three-dimensional object recognition, MIT AI Memo 1239, August 1990.
Edelman, S., H. H. Bülthoff and E. Sklar, Task and object learning in visual recognition, MIT AI Memo 1348, April 1991.
Edelman, S., and D. Weinshall, A self-organizing multiple-view representation of 3D objects, Biological Cybernetics, 64, 209-219, 1991. [see abstract].
Edelman, S., and T. Poggio, Artificial Intelligence -- an update, in Neuroscience Year 1990 (supplement to the Encyclopedia of Neuroscience), B. Smith and G. Adelman, eds., Birkhauser Boston, 1991.
Edelman, S., The features of recognition, Weizmann Institute CS-TR 91-10, 1991.
Edelman, S., and T. Poggio, Representations in high-level vision: reassessing the inverse optics paradigm, Proc. 1989 DARPA Image Understanding Workshop, 944-949.
Poggio, T., and S. Edelman, A network that learns to recognize three-dimensional objects, Nature, 343:263-266, Jan. 1990. [see abstract].
Edelman, S., A network model of object recognition in human vision, in Neural networks for perception, 1:25-40, H. Wechsler, ed., Academic Press, 1991.
Edelman, S., Local qualitative shape from stereo without detailed correspondence, Proc. AAAI-90 Workshop on Qualitative Vision, 101-105, Boston, 1990.
Edelman, S., T. Flash, and S. Ullman, Reading cursive handwriting by alignment of letter prototypes, International Journal of Computer Vision, 5:303-331, 1990.
Edelman, S. Line connectivity algorithms for an asynchronous parallel computer, Computer Vision, Graphics, and Image Processing, 40:169-187, 1987.
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Last modified on Wed Feb 26 09:10:38 2014