• DocumentCode
    3482464
  • Title

    Fuzzy K-NN algorithm using modified K-selection

  • Author

    Kim, Yoon K. ; Han, Joon H.

  • Author_Institution
    Dept. of Comput. Sci., Pohang Inst. of Sci. & Technol., South Korea
  • Volume
    3
  • fYear
    1995
  • fDate
    20-24 Mar 1995
  • Firstpage
    1673
  • Abstract
    In this paper, a new K selection method in fuzzy K-NN (nearest-neighbor) algorithm, called the “updated fuzzy K-NN”, is proposed. The main idea of this method is in the selection of K neighbors by considering the distance difference and the membership grade each neighbor has. The classification results of 32 classes of complex images are given. Compared to K-NN, and fuzzy K-NN algorithm, our method showed improved classification rate
  • Keywords
    fuzzy set theory; image classification; complex images; distance difference; image classification; membership grade; modified K-selection; updated fuzzy K-NN algorithm; Decision theory; Feature extraction; Humans; Nearest neighbor searches; Neural networks; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
  • Conference_Location
    Yokohama
  • Print_ISBN
    0-7803-2461-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.1995.409901
  • Filename
    409901