• DocumentCode
    3236905
  • Title

    Neural Network´s Classification of Terrestrial Surface by Spectral Measuring

  • Author

    Alla, Lavrenuk ; Lilia, Gnibeda ; Katherine, Yarova

  • Author_Institution
    Space Res. Inst., Nat. Acad. of Sci. of Ukraine, Kyiv
  • fYear
    2005
  • fDate
    5-7 Sept. 2005
  • Firstpage
    147
  • Lastpage
    149
  • Abstract
    Intellectual method´s usage for spectral curves analysis is described in article. The method is based on neural networks. The Earth´s surface spectral characteristics estimation is described in this article. Experiments using neural networks were made with different parameters. Various learning methods were used. Neural networks are effective and useful for classification terrestrial surface by spectral measuring.
  • Keywords
    geophysics computing; learning (artificial intelligence); neural nets; pattern classification; remote sensing; spectral analysis; neural network; spectral curve analysis; spectral measurement; surface spectral characteristics estimation; terrestrial surface classification; Earth; Neural networks; Neurons; Pollution measurement; Shape; Snow; Software libraries; Space technology; Vegetation mapping; Water; Distance Earth exploration; neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2005. IDAACS 2005. IEEE
  • Conference_Location
    Sofia
  • Print_ISBN
    0-7803-9445-3
  • Electronic_ISBN
    0-7803-9446-1
  • Type

    conf

  • DOI
    10.1109/IDAACS.2005.282959
  • Filename
    4062110