• DocumentCode
    2036990
  • Title

    Self-learning grid-diagnostic center of telecommunication systems

  • Author

    Dovbysh, A.S. ; Rudenko, M.S.

  • Author_Institution
    Sumy State Univ., Sumy, Ukraine
  • fYear
    2013
  • fDate
    8-14 Sept. 2013
  • Firstpage
    358
  • Lastpage
    359
  • Abstract
    The paper considers the problem of processing and recognition of images of oncological pathology based on the grid system. Some ideas and methods of information-extreme intellectual technology based on maximizing the amount of information are used as algorithms of image processing and recognition. Optimizations of the system of acceptance tolerances with respect to the signs of recognition, the level of selection of standard binary vectors-implementations of images were performed to construct the optimal decision rules of the learning algorithm. The influence of optimizing the brightness characteristics of the images on the accuracy of the recognition has been investigated.
  • Keywords
    cancer; image recognition; learning (artificial intelligence); medical image processing; tumours; vectors; grid system; image processing problem; image recognition problem; information-extreme intellectual technology; learning algorithm; oncological pathology; optimal decision rules; self-learning grid-diagnostic center; standard binary vector selection; telecommunication systems; Abstracts; Automation; Educational institutions; Electronic mail; Image recognition; Pathology; Telecommunications;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Microwave and Telecommunication Technology (CriMiCo), 2013 23rd International Crimean Conference
  • Conference_Location
    Sevastopol
  • Print_ISBN
    978-966-335-395-1
  • Type

    conf

  • Filename
    6652864