A model-based recognition method is introduced which is formulated as an optimization problem. An energy function is derived which represents the constraints on the best solution in order to find the best match. A two-dimensional binary Hopfield neural network is implemented to minimize the energy function. The state of each neuron in the Hopfield network represents the possibility of a match between a node in the model graph and a node in the scene graph.<>


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    Title :

    Object recognition by a Hopfield neural network


    Contributors:
    Nasrabadi, N.M. (author) / Li, W. (author) / Choo, C.Y. (author)


    Publication date :

    1990-01-01


    Size :

    298974 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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