• DocumentCode
    381224
  • Title

    Remote sensing images classification using fuzzy B-spline function neural network

  • Author

    Mao, Jianxu ; Wang, Yaonan ; Sun, Wei

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
  • Volume
    3
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    2159
  • Abstract
    We propose a remote sensing image classification algorithm using the membership function adjustable fuzzy B-spline function neural network. In the proposed classification algorithm, the fuzzy technique and neural network technique are combined, and fuzzy inference is realized by a neural network. The B-spline function is used as the membership function of the fuzzy neural network and its shape can be adjusted in real time, which endows the classifier with better capability of learning and self-adaptiveness. Experimental results show that the proposed classification algorithm can be used in remote sensing image classification, and its classification precision is superior to that of the conventional maximum likelihood algorithm.
  • Keywords
    fuzzy neural nets; image classification; inference mechanisms; learning (artificial intelligence); real-time systems; remote sensing; splines (mathematics); uncertainty handling; experimental results; fuzzy B-spline function neural network; fuzzy inference; learning; maximum likelihood algorithm; membership function; real time; remote sensing image classification; self-adaptive system; Classification algorithms; Fuzzy control; Fuzzy neural networks; Image classification; Inference algorithms; Neural networks; Remote sensing; Shape control; Space technology; Spline;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
  • Print_ISBN
    0-7803-7268-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2002.1021468
  • Filename
    1021468