• DocumentCode
    3064684
  • Title

    Multi-sensor data fusion using neural networks

  • Author

    Fincher, D. Wade ; Mix, Dwight F.

  • Author_Institution
    Dept. of Electr. Eng., Arkansas Univ., Fayetteville, AR, USA
  • fYear
    1990
  • fDate
    4-7 Nov 1990
  • Firstpage
    835
  • Lastpage
    838
  • Abstract
    A general approach to the use of neural networks for data fusion is outlined. The discussion begins with examples of data fusion problems and a pattern recognition example is given to illustrate the concepts involved in data fusion. The differences between using post- and pre-detection signals and the advantages of using the latter are discussed. How to apply a neural network to the data fusion problem is demonstrated, and experimental results for a character recognition task are given. The general approach applies to a variety of practical situations, including robot navigation and military environment assessment/evaluation
  • Keywords
    character recognition; computer vision; neural nets; pattern recognition; character recognition; computer vision; multisensor data fusion; neural networks; pattern recognition; Bayesian methods; Character recognition; Cost function; Modems; Neural networks; Pattern recognition; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 1990. Conference Proceedings., IEEE International Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    0-87942-597-0
  • Type

    conf

  • DOI
    10.1109/ICSMC.1990.142240
  • Filename
    142240