Observations on Cortical Mechanisms for Object Recognition andsLearning

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7217

Full metadata record

DC Field	Value	Language
dc.creator	Poggio, Tomaso	-
dc.creator	Hurlbert, Anya	-
dc.date	2004-10-20T20:50:04Z	-
dc.date	2004-10-20T20:50:04Z	-
dc.date	1993-12-01	-
dc.date.accessioned	2013-10-09T02:48:35Z	-
dc.date.available	2013-10-09T02:48:35Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1404	-
dc.identifier	CBCL-077	-
dc.identifier	http://hdl.handle.net/1721.1/7217	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	This paper sketches a hypothetical cortical architecture for visual 3D object recognition based on a recent computational model. The view-centered scheme relies on modules for learning from examples, such as Hyperbf-like networks. Such models capture a class of explanations we call Memory-Based Models (MBM) that contains sparse population coding, memory-based recognition, and codebooks of prototypes. Unlike the sigmoidal units of some artificial neural networks, the units of MBMs are consistent with the description of cortical neurons. We describe how an example of MBM may be realized in terms of cortical circuitry and biophysical mechanisms, consistent with psychophysical and physiological data.	-
dc.format	24 p.	-
dc.format	272626 bytes	-
dc.format	1060397 bytes	-
dc.format	application/octet-stream	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1404	-
dc.relation	CBCL-077	-
dc.subject	object recognition	-
dc.subject	IT cortex	-
dc.subject	view invariance	-
dc.title	Observations on Cortical Mechanisms for Object Recognition andsLearning	-
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