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dc.contributor.advisorTomaso Poggio
dc.contributor.authorTan, Chestonen_US
dc.contributor.authorLeibo, Joel Zen_US
dc.contributor.authorPoggio, Tomasoen_US
dc.contributor.otherCenter for Biological and Computational Learning (CBCL)en_US
dc.date.accessioned2012-06-21T19:45:06Z
dc.date.available2012-06-21T19:45:06Z
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/1721.1/71199
dc.description.abstractIn recent years, scientific and technological advances have produced artificial systems that have matched or surpassed human capabilities in narrow domains such as face detection and optical character recognition. However, the problem of producing truly intelligent machines still remains far from being solved. In this chapter, we first describe some of these recent advances, and then review one approach to moving beyond these limited successes---the neuromorphic approach of studying and reverse-engineering the networks of neurons in the human brain (specifically, the visual system). Finally, we discuss several possible future directions in the quest for visual intelligence.en_US
dc.description.sponsorshipThis research was sponsored by grants from DARPA (IPTO and DSO), National Science Foundation (NSF-0640097, NSF-0827427), AFSOR-THRL (FA8650-05-C-7262). Additional support was provided by: Adobe, Honda Research Institute USA, King Abdullah University Science and Technology grant to B. DeVore, NEC, Sony and especially by the Eugene McDermott Foundation.en_US
dc.format.extent15 p.en_US
dc.relation.ispartofseriesMIT-CSAIL-TR-2012-016
dc.relation.ispartofseriesCBCL-309
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Unporteden
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectVisionen_US
dc.subjectArtificial intelligenceen_US
dc.titleThrowing Down the Visual Intelligence Gauntleten_US
dc.identifier.citationMachine Learning for Computer Vision (2012); eds: Cipolla R, Battiato S, Giovanni Maria F. Springer: Studies in Computational Intelligence Vol. 411.en_US
dc.language.rfc3066en-US


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