• DocumentCode
    295767
  • Title

    Adaptive classification of hand movement

  • Author

    Holden, Eun- Jung ; Roy, Geoffrey G. ; Owens, Robyn

  • Author_Institution
    Dept. of Comput. Sci., Western Australia Univ., Nedlands, WA, Australia
  • Volume
    3
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    1373
  • Abstract
    The hand sign classification system classifies hand movement data into Australian Sign Language (AUSLAN) signs. It is built as a fuzzy expert system with an adaptive engine that trains the system to handle variations in the movement data, or to adapt to differences amongst signers. Adaptive fuzzy systems are often compared with neural networks in their adaptability, but unlike neural networks, expert knowledge can be imposed onto the system in the form of rules
  • Keywords
    adaptive systems; expert systems; fuzzy systems; handicapped aids; pattern classification; AUSLAN; Australian Sign Language signs; adaptive classification; adaptive fuzzy system; fuzzy expert system; hand sign classification system; knowledge representation; Adaptive systems; Fingers; Fuzzy systems; Handicapped aids; Hybrid intelligent systems; Image recognition; Kinematics; Neural networks; Shape; Virtual reality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.487358
  • Filename
    487358