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

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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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