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Author(s): Kane, J.S. | Paquin, M.J. |
Year: 1993
Citation: IEEE Transactions on Neural Networks, vol.4, no.4, pp.695-702
Abstract: Adaptive resonance architectures are neural nets that are capable of classifying arbitrary input patterns into stable category representations. A hybrid optoelectronic implementation utilizing an optical joint transform correlator is proposed and demonstrated. The resultant optoelectronic system is able to reduce the number of calculations compared to a strictly computer-based approach. The result is that, for larger images, the optoelectronic system is faster than the computer-based approach.
Topics:
Image Analysis,
Applications:
Character Recognition,
Models:
ART 2-A,
