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Integrated cognitive architecture for image understanding using fuzzy clustering and structured neural network

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5 Author(s)
Sawaragi, T. ; Dept. of Eng.-Econ. Syst., Stanford Univ., CA, USA ; Shibata, K. ; Katai, O. ; Iwai, S.
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The authors present an architecture for an integrated image understanding system, in which the following two aspects of human uncertainty-handling in visual information processing are modeled: feature extraction from fuzzy input images, and consistent interpretation by dynamically reducing uncertainties contained in the images. An integrated cognitive architecture is proposed, in which both aspects are modeled by using fuzzy clustering methods and a structured neural network, respectively, which are jointed and coupled to realize the cooperative understanding of an image. The system was implemented for understanding geological images obtained from remote-sensing satellites

Published in:

Fuzzy Systems, 1992., IEEE International Conference on

Date of Conference:

8-12 Mar 1992