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SAIM: A model of visual attention and neglect

  • Part VI: Speech, Vision, and Pattern Recognition
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Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

This paper examines the reason for a particular impairment of cognitive functioning in brain-damaged patients called visual neglect. To achieve this goal a Selective Attention Identification Model (SAIM) was developed which performs translation-invariant object recognition. SAIM uses a constraint satisfaction routine based on a continuous Hopfield network to map an object into a focus of attention. The simulation results show that SAIM is a successful model of visual attention and visual neglect.

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Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Heinke, D., Humphreys, G.W. (1997). SAIM: A model of visual attention and neglect. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020269

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  • DOI: https://doi.org/10.1007/BFb0020269

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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