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Article #1301preprint - Complex Cells and Object Recognition
From: Shimon Edelman
Date: Fri, 23 May 1997 00:00
Date: Fri, 23 May 1997 00:00
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1670 bytes
ftp URL: ftp://eris.wisdom.weizmann.ac.il/pub/edelman/nips97.ps.Z http URL: http://www.ai.mit.edu/~edelman/mirror/nips97.ps.Z Abstract: Nearest-neighbor correlation-based similarity computation in the space of outputs of complex-type receptive fields can support robust recognition of 3D objects. Our experiments with four collections of objects resulted in mean recognition rates between 84% (for subordinate-level discrimination among 15 quadruped animal shapes) and 94% (for basic-level recognition of 20 everyday objects), over a 40deg X 40deg range of viewpoints, centered on a stored canonical view and related to it by rotations in depth. This result has interesting implications for the design of a front end to an artificial object recognition system, and for the understanding of the faculty of object recognition in primate vision. ------------------------------------------------------------------------ Comments welcome. -Shimon Dr. Shimon Edelman, Center for Biol & Comp Learning, MIT DELENDA BIBI http://www.ai.mit.edu/~edelman fax: (+1) 617 253-2964 tel: 253-6357 edelman@ai.mit.edu
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X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 108436,221245c0764d514e,start X-Google-Attributes: gid108436,public From: Shimon Edelman <edelman@ai.mit.edu> Subject: preprint - Complex Cells and Object Recognition Date: 1997/05/23 Message-ID: <199705231837.OAA04793@it-cortex> X-Deja-AN: 243571297 Title: Complex Cells and Object Recognition To: connectionists@cs.cmu.edu Authors: Shimon Edelman, Nathan Intrator, Tomaso Poggio Reply-To: neuras-list@etsiig.uniovi.es Newsgroups: es.comp.neuronal