• DocumentCode
    2787246
  • Title

    InFuse-an integrated expert neural network for intelligent sensor fusion

  • Author

    Bailey, Gretchen D. ; Raghavan, Srinivasan ; Gupta, Naresh ; Lambird, Barbara ; Lavine, David

  • Author_Institution
    LNK Corp., Riverdale, MD, USA
  • fYear
    1991
  • fDate
    30 Sep-2 Oct 1991
  • Firstpage
    196
  • Lastpage
    201
  • Abstract
    A discussion is presented of an architecture called InFuse (Intelligent Fusion) for the multiple sensor fusion problem. InFuse exploits the notion of combining expert systems and neural networks to capture the advantages of both technologies. The application involves the extraction of natural terrain features from imagery provided by multiple sensors. In addition to the imagery, terrain knowledge in geographical databases needs to be integrated. The uniqueness of the approach lies in its ability to combine symbolic data of spatial databases and domain-specific knowledge about sensor behavior in expert systems with example-induced learning from neural networks to achieve a high classification rate. Results are presented to demonstrate the power of the approach
  • Keywords
    computerised picture processing; database management systems; expert systems; geographic information systems; learning systems; neural nets; InFuse; Intelligent Fusion; domain-specific knowledge; example-induced learning; expert systems; geographical databases; imagery; integrated expert neural network; intelligent sensor fusion; multiple sensor fusion problem; natural terrain features extraction; spatial databases; symbolic data; terrain knowledge; Data mining; Expert systems; Image databases; Image sensors; Intelligent sensors; Neural networks; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Developing and Managing Expert System Programs, 1991., Proceedings of the IEEE/ACM International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-8186-2250-4
  • Type

    conf

  • DOI
    10.1109/DMESP.1991.171737
  • Filename
    171737