Deconvolution as a model of blur adaptation in the visual cortex

László Orzó, Antal Hiba, Ákos Zarándy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The development of Cellular Neural Networks are a special example, how the application of new image processing architectures and techniques can help to understand the operation of real neural networks. Especially, here we investigated the neural blur adaptation. We propose a deconvolution based model to account this phenomena. We show that this model can have a more or less plausible neural implementation. Special properties and a potential application of the proposed model is outlined too.

Original languageEnglish
Title of host publicationCNNA 2016 - 15th International Workshop on Cellular Nanoscale Networks and Their Applications
EditorsRonald Tetzlaff
PublisherIEEE Computer Society
Pages47-48
Number of pages2
ISBN (Electronic)9783800742523
Publication statusPublished - Jan 1 2016
Event15th International Workshop on Cellular Nanoscale Networks and Their Applications, CNNA 2016 - Dresden, Germany
Duration: Aug 23 2016Aug 25 2016

Publication series

NameInternational Workshop on Cellular Nanoscale Networks and their Applications
Volume2016-August
ISSN (Print)2165-0160
ISSN (Electronic)2165-0179

Conference

Conference15th International Workshop on Cellular Nanoscale Networks and Their Applications, CNNA 2016
CountryGermany
CityDresden
Period8/23/168/25/16

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

Orzó, L., Hiba, A., & Zarándy, Á. (2016). Deconvolution as a model of blur adaptation in the visual cortex. In R. Tetzlaff (Ed.), CNNA 2016 - 15th International Workshop on Cellular Nanoscale Networks and Their Applications (pp. 47-48). (International Workshop on Cellular Nanoscale Networks and their Applications; Vol. 2016-August). IEEE Computer Society.