• DocumentCode
    2091305
  • Title

    Land cover classification by using screening and truncated normal distribution

  • Author

    Hosomura, Tsukasa

  • Author_Institution
    Dept. of Inf. & Arts, Tokyo Denki Univ., Saitama, Japan
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    199
  • Abstract
    In this paper, in order to improve the classification accuracy training data screening and truncated normal distribution maximum likelihood classification are adopted. We verify these techniques are effective measures for the improvement in the classification accuracy
  • Keywords
    geography; image classification; normal distribution; remote sensing; land cover classification; maximum likelihood classification; screening; truncated normal distribution; Art; Classification algorithms; Data mining; Equations; Gaussian distribution; Humans; Probability density function; Probability distribution; Tail; Training data;
  • 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.2001.976101
  • Filename
    976101
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2091305