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Shape Representation in V4: Investigating Position-Specific Tuning for Boundary Conformation with the Standard Model of Object Recognition

dc.date.accessioned2005-12-22T02:15:22Z
dc.date.accessioned2018-11-24T10:24:18Z
dc.date.available2005-12-22T02:15:22Z
dc.date.available2018-11-24T10:24:18Z
dc.date.issued2004-11-12
dc.identifier.urihttp://hdl.handle.net/1721.1/30501
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/30501
dc.description.abstractThe computational processes in the intermediate stages of the ventral pathway responsible for visual object recognition are not well understood. A recent physiological study by A. Pasupathy and C. Connor in intermediate area V4 using contour stimuli, proposes that a population of V4 neurons display bjectcentered,position-specific curvature tuning [18]. The  standard model of object recognition, a recently developed model [23] to account for recognition properties of IT cells (extending classical suggestions by Hubel, Wiesel and others [9, 10, 19]), is used here to model the response of the V4 cells described in [18]. Our results show that a feedforward, network level mechanism can exhibit selectivity and invariance properties that correspond to the responses of the V4 cells described in [18]. These results suggest howobject-centered, position-specific curvature tuning of V4 cells may arise from combinations of complex V1 cell responses. Furthermore, the model makes predictions about the responses of the same V4 cells studied by Pasupathy and Connor to novel gray level patterns, such as gratings and natural images. Thesepredictions suggest specific experiments to further explore shape representation in V4.
dc.format.extent12 p.
dc.format.extent38801213 bytes
dc.format.extent5292186 bytes
dc.language.isoen_US
dc.subjectAI
dc.subjectV4 Visual Cortex Object Recognition Standard Model
dc.titleShape Representation in V4: Investigating Position-Specific Tuning for Boundary Conformation with the Standard Model of Object Recognition


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