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(p)Reprints available for downloading:
Oren Kolodny, Shimon Edelman, and Arnon Lotem, Evolution of
continuous learning of the structure of the environment, Journal of
the Royal Society Interface, in press.
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).
Shimon Edelman and Reza Shahbazi, Renewing the Respect for
Similarity, Frontiers in Computational Neuroscience (part of a
Frontiers Research Topic,
Recognition of Visual Objects), 6:45 (2012).
Shimon Edelman, Vision, reanimated and reimagined, (special issue
on the 30th anniversary of the publication of Marr's Vision),
Perception, 41:1116-1127 (2012).
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.
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
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).
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
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 http://journalsonline.tandf.co.uk.
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
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).
Shimon Edelman, Mostly Harmless (review of Action in
Perception by Alva Noë, MIT Press, 2005);
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
The interaction of shape- and location-based priming in object
categorisation: Evidence for a hybrid "what+where" representation
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.
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].
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
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
workshop (Whistler, BC, Dec. 2003)
nature of language
Shimon Edelman, A New Vision of Language:
abstract of a talk
presented at the 25th Conference of the
Cognitive Science Society (Boston, MA, July 2003);
the slides of
the CogSci'03 talk;
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.
Ian M. Thornton, Martin A. Giese and Shimon Edelman, Representing
biological motion, Proc. ECVP'03, Perception, September 2003.
Martin A. Giese, Ian M. Thornton and Shimon Edelman, Metric
category spaces of biological motion, Proc. VSS'03, Journal of
Vision, May 2003.
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].
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
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].
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
Shimon Edelman, Constraining the neural
representation of the visual world, Trends in Cognitive Sciences 6:125-131, 2002
Edelman, S., and N. Intrator, Models of perceptual learning,
in Perceptual learning, M. Fahle and T. Poggio, eds., MIT Press,
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].
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
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).
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
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
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]
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).
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).
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].
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,
and Brain Sciences 21:449-498, 1998 [see abstract;
the RESPONSE to the commentaries
Cutzu, F., and S. Edelman, Representation of object similarity
in human vision: psychophysics and a computational model, Vision
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]
Edelman, S., Computational theories of object recognition,
Trends in Cognitive Sciences, 1:296-304, 1997 [see abstract]
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,
Karov, Y., and S. Edelman, Similarity-based word sense disambiguation,
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
Intrator N., S. Edelman and H. H. Bülthoff, An integrated approach
to the study of object features in visual recognition, Network
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
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
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.
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.
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.
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,
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
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
Poggio, T., and S. Edelman, A network that learns to recognize
three-dimensional objects, Nature, 343:263-266, Jan. 1990.
Edelman, S., A network model of object recognition in human vision,
in Neural networks for perception, 1:25-40, H. Wechsler, ed., Academic
Edelman, S., Local qualitative shape from stereo without detailed
correspondence, Proc. AAAI-90 Workshop on Qualitative Vision, 101-105,
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 Tue Dec 3 08:00:57 2013