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Median Hetero-Associative Memories Applied to the Categorization of True-Color Patterns

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6077))

Abstract

Median associative memories (MED-AMs) are a special type of associative memory based on the median operator. This type of associative model has been applied to the restoration of gray scale images and provides better performance than other models, such as morphological associative memories, when the patterns are altered with mixed noise. Despite of his power, MED-AMs have not been applied in problems involving true-color patterns. In this paper we describe how a median hetero-associative memory (MED-HAM) could be applied in problems that involve true-color patterns. A complete study of the behavior of this associative model in the restoration of true-color images is performed using a benchmark of 14400 images altered by different type of noises. Furthermore, we describe how this model can be applied to an image categorization problem.

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Vázquez, R.A., Sossa, H. (2010). Median Hetero-Associative Memories Applied to the Categorization of True-Color Patterns. In: Corchado, E., Graña Romay, M., Manhaes Savio, A. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13803-4_52

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  • DOI: https://doi.org/10.1007/978-3-642-13803-4_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13802-7

  • Online ISBN: 978-3-642-13803-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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