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International Work-Conference on Artificial Neural Networks

IWANN 1997: Biological and Artificial Computation: From Neuroscience to Technology pp 872–881Cite as

Constrained neural network for estimating sensor reliability in sensors fusion

  • Methodology for Data Analysis, Task Selection and Nets Design
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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1240))

Abstract

In sensors fusion, “Context Dependent” fusion operators represent a very powerful approach. Most often, context is related to the reliability of the sensors. This approach is efficient if the estimation of the sensors reliability is itself reliable. We show how this has been done thanks to an optimal non-linear data transformation by ANN. An application in audio-visual speech recognition will illustrate this implementation.

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References

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Authors and Affiliations

  1. Laboratoire de Traitement d'Images et de Reconnaissance des Formes, LTIRF, INPG, 46 Av. Félix-Viallet, 38031, Grenoble Cedex 1

    Anne Guérin-Dugué, Pascal Teissier & Jeanny Hérault

  2. Institut de la Communication Parlée, CNRS UPRESA 5009/INPG-U. Stendhal ICP, INPG, 46 Av. Félix-Viallet, 38031, Grenoble Cedex 1

    Pascal Teissier & Jean-Luc Schwartz

Authors
  1. Anne Guérin-Dugué
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  2. Pascal Teissier
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  3. Jean-Luc Schwartz
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  4. Jeanny Hérault
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Editor information

José Mira Roberto Moreno-Díaz Joan Cabestany

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© 1997 Springer-Verlag Berlin Heidelberg

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Guérin-Dugué, A., Teissier, P., Schwartz, JL., Hérault, J. (1997). Constrained neural network for estimating sensor reliability in sensors fusion. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032547

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  • DOI: https://doi.org/10.1007/BFb0032547

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63047-0

  • Online ISBN: 978-3-540-69074-0

  • eBook Packages: Springer Book Archive

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