• DocumentCode
    2050022
  • Title

    Investigations of the self organising tree map

  • Author

    Randall, Jonathan ; Guan, Ling ; Zhang, Xing ; Li, Wanqing

  • Author_Institution
    Dept. of Electr. Eng., Sydney Univ., NSW, Australia
  • Volume
    2
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    724
  • Abstract
    The self-organising tree map (SOTM), which is a variation of the self-organising map, is studied for the purpose of unsupervised data clustering. This method is applied to segmentation of grey-scale digital images, and the properties of the map are illustrated by clustering of uniformly distributed two-dimensional squares
  • Keywords
    image segmentation; pattern clustering; self-organising feature maps; trees (mathematics); unsupervised learning; grey-scale digital image segmentation; self-organising tree map; uniformly distributed squares; unsupervised data clustering; Clustering algorithms; Computer architecture; Convergence; Degradation; Digital images; Distributed computing; Electronic mail; Euclidean distance; Image segmentation; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-5871-6
  • Type

    conf

  • DOI
    10.1109/ICONIP.1999.845685
  • Filename
    845685