Covert Attention with a Spiking Neural Network View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2008

AUTHORS

Sylvain Chevallier , Philippe Tarroux

ABSTRACT

We propose an implementation of covert attention mechanisms with spiking neurons. Spiking neural models describe the activity of a neuron with precise spike-timing rather than firing rate. We investigate the interests offered by such a temporal code for low-level vision and early attentional process. This paper describes a spiking neural network which achieves saliency extraction and stable attentional focus of a moving stimulus. Experimental results obtained using real visual scene illustrate the robustness and the quickness of this approach. More... »

PAGES

56-65

References to SciGraph publications

  • 2001-11. Saliency, Scale and Image Description in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2007. Liquid Computing in COMPUTATION AND LOGIC IN THE REAL WORLD
  • 1996-06. Speed of processing in the human visual system in NATURE
  • 2001-03. Computational modelling of visual attention in NATURE REVIEWS NEUROSCIENCE
  • 2000-05. Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons in JOURNAL OF COMPUTATIONAL NEUROSCIENCE
  • 2000-06. Evaluation of Interest Point Detectors in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004-06. Finding independent components using spikes: A natural result of hebbian learning in a sparse spike coding scheme in NATURAL COMPUTING
  • 1992-01. On the relative complexity of active vs. passive visual search in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • Book

    TITLE

    Computer Vision Systems

    ISBN

    978-3-540-79546-9
    978-3-540-79547-6

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-79547-6_6

    DOI

    http://dx.doi.org/10.1007/978-3-540-79547-6_6

    DIMENSIONS

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