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Proceedings Paper

Neuronal networks for pattern recognition
Author(s): Manfred Rueff; Manfred Schmutz
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Paper Abstract

To make efficient practical use of the attractive properties of standard neural network models it seems reasonable to com bine a recognition network with appropiate conventional preprocessing. In this contribution we describe the current research at IPA concerning such a hybrid approach to acoustic pattern recognition. The inputs of the recognition network are feature vectors consisting of local frequency characteristics extracted from the Wigner representation of the patterns. Simulations show that the system is capable to recognize individually learned objects in a scene.

Paper Details

Date Published: 1 August 1990
PDF: 8 pages
Proc. SPIE 1265, Industrial Inspection II, (1 August 1990); doi: 10.1117/12.20238
Show Author Affiliations
Manfred Rueff, IPA Stuttgart (Germany)
Manfred Schmutz, IPA Stuttgart (Germany)


Published in SPIE Proceedings Vol. 1265:
Industrial Inspection II
Donald W. Braggins, Editor(s)

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