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Image Processing Using RBF like Neural Networks: A ZISC-036 Based Fully Parallel Implementation Solving Real World and Real Complexity Industrial Problems

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Abstract

The present article concerns neural based image processing and solutions developed for industrial problems using the ZISC-036 neuro-processor, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm (RCE) and the K-Nearest Neighbor algorithm (KNN). The developed neural based techniques have been applied for image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). We also have developed and implemented on ZISC-036 neuro-processor, a neural network based solution for visual probe mark inspection in VLSI production for the IBM Essonnes plant. The main characteristics of such systems are real-time control and high reliability in detection and classification tasks. Experimental results, validating presented concepts, have been reported showing quantitative and qualitative improvement as well as the efficiency our solutions.

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Authors and Affiliations

  1. Intelligence in Instrumentation and Systems—I2S, SENART Institute of Technology, University PARIS XII, Avenue Pierre POINT-F-77127, LIEUSAINT, France

    Kurosh Madani

  2. IBM France, Laboratoire d'Etude et de Developpement, 224, boulevard John Kennedy, F-91105, Corbeil Essonnes Cedex, France

    Ghislain de Trémiolles & Pascal Tannhof

Authors
  1. Kurosh Madani
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  2. Ghislain de Trémiolles
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  3. Pascal Tannhof
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Madani, K., de Trémiolles, G. & Tannhof, P. Image Processing Using RBF like Neural Networks: A ZISC-036 Based Fully Parallel Implementation Solving Real World and Real Complexity Industrial Problems. Applied Intelligence 18, 195–213 (2003). https://doi.org/10.1023/A:1021990410058

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  • DOI: https://doi.org/10.1023/A:1021990410058

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