• DocumentCode
    1576147
  • Title

    Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification

  • Author

    Martin, Arnaud ; Osswald, Christophe

  • Author_Institution
    ENSIETA, Brest
  • fYear
    2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account the uncertainty of the reality in the learning stage. The results of this seabed characterization are presented on real sonar images.
  • Keywords
    belief networks; image classification; learning (artificial intelligence); multilayer perceptrons; sonar imaging; belief learning; multilayer perceptron; sonar image classification; Classification algorithms; Humans; Image classification; Multilayer perceptrons; Pixel; Possibility theory; Sediments; Sonar navigation; Tiles; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on
  • Conference_Location
    Damascus
  • Print_ISBN
    978-1-4244-1751-3
  • Electronic_ISBN
    978-1-4244-1752-0
  • Type

    conf

  • DOI
    10.1109/ICTTA.2008.4530035
  • Filename
    4530035