• DocumentCode
    2104758
  • Title

    A data-fusion approach to partially supervised classification

  • Author

    Prieto, Diego Fernàndez ; Arino, Olivier

  • Author_Institution
    Earth Obs. Applications Dept., Eur. Space Agency, Frascati, Italy
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    858
  • Abstract
    Considers the problem of partially supervised classification under a data-fusion perspective. The objective is to map one class (or only few classes) of interest in multisensor remote-sensing data by using exclusively training samples belonging to such class (or classes). The proposed methodology is based on a combined use of a radial basis function (RBF)-like network and a Markov random field (MRF) approach
  • Keywords
    sensor fusion; terrain mapping; Markov random field; data fusion; land cover; multisensor remote sensing data; partially supervised classification; radial basis function; Earth; Forestry; Impedance; Information analysis; Layout; Markov random fields; Maximum likelihood estimation; Remote sensing; Statistical analysis; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    0-7803-7031-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2001.976660
  • Filename
    976660
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2104758