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

dc.date.accessioned2004-10-20T21:04:02Z
dc.date.accessioned2018-11-24T10:23:30Z
dc.date.available2004-10-20T21:04:02Z
dc.date.available2018-11-24T10:23:30Z
dc.date.issued1997-08-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7247
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7247
dc.description.abstractStimuli 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.en_US
dc.format.extent309472 bytes
dc.format.extent368749 bytes
dc.language.isoen_US
dc.titleVisual Segmentation without Classification in a Model of the Primary Visual Cortexen_US


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