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Proceedings Paper

Model for a color perception system with learning capabilities
Author(s): Michael Frydrych; Jussi P. S. Parkkinen; Sinikka Parkkinen; Pertti Silfsten; Timo Jaeaeskelaeinen
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Paper Abstract

We present a model for color vision system with learning capabilities. The system adapts to statistical properties of its input. The adaptation is done by utilizing unsupervised learning techniques, as self-organizing feature maps and vectorial boundary adaptation maps. A color difference reflecting statistical properties of input to the system is defined. The model was tested by using color data with different statistics and two different sets of rhodopsin- based color sensors.

Paper Details

Date Published: 1 April 1998
PDF: 10 pages
Proc. SPIE 3402, Optical Information Science and Technology (OIST97): Optical Memory and Neural Networks, (1 April 1998); doi: 10.1117/12.304979
Show Author Affiliations
Michael Frydrych, Lappeenranta Univ. of Technology (Finland)
Jussi P. S. Parkkinen, Lappeenranta Univ. of Technology (Finland)
Sinikka Parkkinen, Lappeenranta Univ. of Technology (Finland)
Pertti Silfsten, Lappeenranta Univ. of Technology (Finland)
Timo Jaeaeskelaeinen, Univ. of Joensuu (Finland)

Published in SPIE Proceedings Vol. 3402:
Optical Information Science and Technology (OIST97): Optical Memory and Neural Networks
Andrei L. Mikaelian, Editor(s)

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