• DocumentCode
    843719
  • Title

    Maximum a posteriori approach to object recognition with distributed sensors

  • Author

    Demirbas, K.

  • Author_Institution
    Illinois Univ., Chicago, IL
  • Volume
    24
  • Issue
    3
  • fYear
    1988
  • fDate
    5/1/1988 12:00:00 AM
  • Firstpage
    309
  • Lastpage
    313
  • Abstract
    The maximum a posteriori (MAP) estimation concept is applied to the problem of object recognition with several distributed sensors. It is shown that in binary object recognition the MAP object recognition also minimizes the mean-square error. Simulation results show that the performance of the MAP object recognition is, in general, at least as good as the best performance by the sensors used
  • Keywords
    pattern recognition; picture processing; MAP; binary object recognition; distributed sensors; estimation concept; maximum a posteriori; mean-square error; object recognition; performance; Cost function; Degradation; Density functional theory; Density measurement; Image recognition; Image sensors; Noise robustness; Object detection; Object recognition; Testing;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/7.192105
  • Filename
    192105
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=843719