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Neural Systems for Motion Analysis: Single Neuron and Network Approaches

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Soft Computing for Image Processing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 42))

Abstract

This chapter employs large-scale computer simulations to investigate properties of the visual cortex, in particular the motion pathway. We have modeled the direction and orientation sensitive portions of the pathway using a biological model of the dendritic structure of a neuron and with a Jordan-Elman recurrent network. While biologically motivated, our study is not meant to imply a functional underlying architecture based on our simulations, but to provide a computational system for possible use in machine vision applications. The construction and simulation of large-scale neuronal networks using simplified models is governed by the tradeoff between biological fidelity for a full model and the decrease in computational complexity for the simplified one.

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Author information

Authors and Affiliations

  1. Intelligent Systems Laboratory, Department of Computer Science, University of South Carolina, Columbia, SC 29208, USA

    Terry L. Huntsberger, John R. Rose & Dudley Girard

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  1. Terry L. Huntsberger
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  2. John R. Rose
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  3. Dudley Girard
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Editors and Affiliations

  1. Machine Intelligence Unit, Indian Statistical Institute, 203 B. T. Road, Calcutta, 700035, India

    Sankar K. Pal , Ashish Ghosh  & Malay K. Kundu ,  & 

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Huntsberger, T.L., Rose, J.R., Girard, D. (2000). Neural Systems for Motion Analysis: Single Neuron and Network Approaches. In: Pal, S.K., Ghosh, A., Kundu, M.K. (eds) Soft Computing for Image Processing. Studies in Fuzziness and Soft Computing, vol 42. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1858-1_20

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  • DOI: https://doi.org/10.1007/978-3-7908-1858-1_20

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2468-1

  • Online ISBN: 978-3-7908-1858-1

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