• DocumentCode
    2350817
  • Title

    Techniques for neural network identification of phytoplankton for the EurOPA flow cytometer

  • Author

    Boddy, L. ; Wilkins, M.F. ; Morris, C.W. ; Tarran, G.A. ; Burkill, P.H. ; Jonker, R.R.

  • Author_Institution
    Sch. of Pure & Applied Biol., Univ. of Wales Coll. of Cardiff, UK
  • Volume
    1
  • fYear
    1994
  • fDate
    13-16 Sep 1994
  • Abstract
    The EurOPA instrument is a purpose-built marine flow cytometer to be taken to sea for rapid analysis of seawater samples for phytoplankton content. To take advantage of the potentially high rate of data capture, neural network classifiers will be incorporated into the package to provide an integrated approach to plankton analysis
  • Keywords
    aquaculture; biological techniques; geophysical signal processing; neural nets; oceanographic techniques; pattern classification; EurOPA flow cytometer; biophysical measurement technique; classifier; geophysics computing; instrument; marine biology; monitoring; neural net; neural network identification; ocean; optical method; phytoplankton; plankton; sea; seawater sample; signal processing; Artificial neural networks; Biology computing; Fluorescence; Image motion analysis; Instruments; Marine vegetation; Neural networks; Optical scattering; Particle measurements; Sea measurements;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    OCEANS '94. 'Oceans Engineering for Today's Technology and Tomorrow's Preservation.' Proceedings
  • Conference_Location
    Brest
  • Print_ISBN
    0-7803-2056-5
  • Type

    conf

  • DOI
    10.1109/OCEANS.1994.363967
  • Filename
    363967