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Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition

  • Simei Gomes Wysoski
  • Lubica Benuskova
  • Nikola Kasabov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4985)

Abstract

The paper describes the integration of brain-inspired systems to perform audiovisual pattern recognition tasks. Individual sensory pathways as well as the integrative modules are implemented using a fast version of spiking neurons grouped in evolving spiking neural network (ESNN) architectures capable of lifelong adaptation. We design a new crossmodal integration system, where individual modalities can influence others before individual decisions are made, fact that resembles some characteristics of the biological brains. The system is applied to the person authentication problem. Preliminary results show that the integrated system can improve the accuracy in many operation points as well as it enables a range of multi-criteria optimizations.

Keywords

Spiking Neural Networks Multi-modal Information Processing Face and Speaker Recognition Visual and Auditory Integration 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Simei Gomes Wysoski
    • 1
  • Lubica Benuskova
    • 1
  • Nikola Kasabov
    • 1
  1. 1.Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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