Visual Segmentation without Classification in a Model of the Primary Visual Cortex

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7247

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DC Field	Value	Language
dc.creator	Li, Zhaoping	-
dc.date	2004-10-20T21:04:02Z	-
dc.date	2004-10-20T21:04:02Z	-
dc.date	1997-08-01	-
dc.date.accessioned	2013-10-09T02:48:46Z	-
dc.date.available	2013-10-09T02:48:46Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1613	-
dc.identifier	CBCL-153	-
dc.identifier	http://hdl.handle.net/1721.1/7247	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	Stimuli outside classical receptive fields significantly influence the neurons' activities in primary visual cortex. We propose that such contextual influences are used to segment regions by detecting the breakdown of homogeneity or translation invariance in the input, thus computing global region boundaries using local interactions. This is implemented in a biologically based model of V1, and demonstrated in examples of texture segmentation and figure-ground segregation. By contrast with traditional approaches, segmentation occurs without classification or comparison of features within or between regions and is performed by exactly the same neural circuit responsible for the dual problem of the grouping and enhancement of contours.	-
dc.format	309472 bytes	-
dc.format	368749 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1613	-
dc.relation	CBCL-153	-
dc.title	Visual Segmentation without Classification in a Model of the Primary Visual Cortex	-
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