Heterogeneous input neuration for network-based object recognition architectures

John F. Gnazzo

doi:10.1117/12.48382

1 October 1991 Heterogeneous input neuration for network-based object recognition architectures

John F. Gnazzo

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48382
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

John F. Gnazzo "Heterogeneous input neuration for network-based object recognition architectures", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48382

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