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Proceedings Paper

Heterogeneous input neuration for network-based object recognition architectures
Author(s): John F. Gnazzo
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Paper Abstract

The utilization of artificial neural networks (ANN) in the area of signal and image processing applications is showing great promise. The simplification of the classical object recognition methodology is illustrated by the network based algorithm development of a simple 2-D character recognition system. The hardware implementation of such a system is also discussed. An example of a network-based solution to a target recognition problem utilizing single sensor acoustic data is also addressed. The term heterogenous input neuration is introduced.

Paper Details

Date Published: 1 October 1991
PDF: 8 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48382
Show Author Affiliations
John F. Gnazzo, Alliant Techsystems Inc. (United States)


Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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