• DocumentCode
    468992
  • Title

    Pulp fibre recognition expert system based on neural network

  • Author

    Lv, Yin-ping ; Qiu, Shu-Bo ; Yuan, Bin

  • Author_Institution
    Shandong Inst. of Light Ind., Jinan
  • Volume
    2
  • fYear
    2007
  • fDate
    2-4 Nov. 2007
  • Firstpage
    788
  • Lastpage
    792
  • Abstract
    The characteristics of pulp fibre influence the final qualities of paper production, but the phenomenon of intersectant, curled and bifurcate of the pulp fibre is very familiar, as a result the routine methods can hardly achieve the analysis and recognition of complex pulp fibre image preferably. The paper introduces the basic principle, structure and recognition tactics of the pulp fibre recognition artificial intelligence expert system based on neural network. According to the characters of pulp fibre, it distinguishes from different levels, The system start the fleet repository to analyze the input simple fibre character, then the system will start the deep repository of expert system to get the result of complex fiber character. From the parallel processing and oneself learning of neural network, it overcomes some insufficiency of traditional recognition methods, obtaining preferable recognition effect.
  • Keywords
    expert systems; image recognition; neural nets; paper industry; artificial intelligence; expert system; neural network; paper production; parallel processing; pulp fibre image recognition; Artificial intelligence; Artificial neural networks; Bifurcation; Character recognition; Expert systems; Image analysis; Image recognition; Neural networks; Parallel processing; Production; Pulp fibre; expert system; neural network; repositor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-1065-1
  • Electronic_ISBN
    978-1-4244-1066-8
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2007.4420776
  • Filename
    4420776