• DocumentCode
    1909084
  • Title

    Multisensor image classification by structured neural networks

  • Author

    Roli, F. ; Serpico, S.B. ; Vernazza, G.

  • Author_Institution
    Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
  • fYear
    1993
  • fDate
    6-9 Sep 1993
  • Firstpage
    311
  • Lastpage
    320
  • Abstract
    The application of structured neural networks to the supervised classification of multisensor images is discussed. The purpose is to give a criterion for network architecture definition and to allow the interpretation of the network behavior. The latter result can be used to understand the importance of sensors and related channels to the classification task. The networks´ architecture is configured by exploiting the characteristics of a given multisensor classification problem. Then, such networks are trained to solve the problem. Finally, they are transformed into equivalent networks to obtain a simplified representation
  • Keywords
    image classification; neural nets; sensor fusion; multisensor image classification; structured neural networks; supervised classification; Artificial neural networks; Backpropagation algorithms; Data mining; Electronic mail; Image classification; Image sensors; Layout; Neural networks; Sensor phenomena and characterization; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop
  • Conference_Location
    Linthicum Heights, MD
  • Print_ISBN
    0-7803-0928-6
  • Type

    conf

  • DOI
    10.1109/NNSP.1993.471857
  • Filename
    471857