Hybrid NN-Bayesian architecture for information fusion

H. Pan, Zhi-Pei Liang, Thomas J Anastasio, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper discusses a novel technique for information fusion. Specifically, a formula is derived for estimation of the joint probabilities in the maximum entropy sense. In addition, neural networks are used to estimate conditional probabilities required in the Bayesian inference method. Preliminary experimental results demonstrate that the proposed method can significantly improve the accuracy of the bimodal recognition system using audio/video signals.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE Comp Soc
Pages368-371
Number of pages4
Volume1
StatePublished - Dec 1 1998
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: Oct 4 1998Oct 7 1998

Other

OtherProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period10/4/9810/7/98

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Pan, H., Liang, Z-P., Anastasio, T. J., & Huang, T. S. (1998). Hybrid NN-Bayesian architecture for information fusion. In IEEE International Conference on Image Processing (Vol. 1, pp. 368-371). IEEE Comp Soc.