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Proceedings Paper

Pixels Classification With Neurocomputer
Author(s): Chung Lin Huang
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Paper Abstract

This paper developes a new method for the pixel classification of an intensity image. A neural networks of non-linear analog neurons have been shown extremely effective. This problem is considered as an optimally classification of an image based on their original activation. Optimization is defined in terms of energy which is a function of neurons the output values which vary continuously. The neurons are modelled as amplifiers which have sigmoid monotonic input-output relations. A synapse between two neurons is defined by a conductance which connects the output of neuron to the input of another neuron. The net input current to any neuron is the sum of the currents flowing through the set of resistors connecting its input to the outputs of the other neurons. We have formulate the problems in terms of desired optima, subject to certain constraints.

Paper Details

Date Published: 1 February 1990
PDF: 8 pages
Proc. SPIE 1197, Automated Inspection and High-Speed Vision Architectures III, (1 February 1990); doi: 10.1117/12.969958
Show Author Affiliations
Chung Lin Huang, National Tsing Hua University (China)

Published in SPIE Proceedings Vol. 1197:
Automated Inspection and High-Speed Vision Architectures III
Michael J. W. Chen, Editor(s)

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