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    •   OpenBU
    • College of Arts and Sciences
    • Cognitive & Neural Systems
    • CAS/CNS Technical Reports
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    Neural Network for Dynamic Binding with Graph Representation: Form, Linking, and Depth-From-Occlusion

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    Date Issued
    1994-10
    Author(s)
    Williamson, James R.
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    Permanent Link
    https://hdl.handle.net/2144/2170
    Abstract
    A neural network is presented which explicity represents form attributes and relations between them, thus solving the binding problem without temporal coding. Rather, the network creates a graph representation by dynamically allocating nodes to code local form attributes and establishing ares to link. With this representation, the network selectivly groups and segments in depth objects based on line junction information, producing results consistent with those of several recent visual search eperiments. In addiction to depth-from-occlusion, the network provides a sufficient framework for local line-labelling processes to recover other 3-D variables, such as edge/surface contiguity, edge, slant, and edge convexity.
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    Copyright 1994 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.
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    • CAS/CNS Technical Reports [485]


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