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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 30132


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15671
Integrating Low and High Level Object Recognition Steps by Probabilistic Networks
Abstract:
In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Digital Object Identifier (DOI):

References:

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