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Proceedings Paper

Artificial neural network and image processing using the Adaptive Solutions' architecture
Author(s): Thomas E. Baker
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Paper Abstract

Adaptive Solutions' CNAPS architecture is a parallel array of digital processors. This design features a Single-Instruction Multiple-Data (SIMD) stream architecture. The architecture is designed to execute on- chip learning for Artificial Neural Network (ANN) algorithms with unprecedented performance. ANNs have shown impressive results for solving difficult image processing tasks. However, current hardware prevents many ANN solutions from being effective products. The CNAPS architecture will provide the computational power to allow real time ANN applications. Because of the high parallelism of the architecture,it is also ideal for digital image processing tasks. This architecture will allow high performance applications that combine conventional image processing methods and ANNs on the same system. This paper gives a brief introduction to the CNAPS architecture, and gives the system performance on implementation of neural network algorithms, and conventional image processing algorithms such as convolution, and 2D Fourier transforms.

Paper Details

Date Published: 1 June 1991
PDF: 10 pages
Proc. SPIE 1452, Image Processing Algorithms and Techniques II, (1 June 1991); doi: 10.1117/12.45409
Show Author Affiliations
Thomas E. Baker, Adaptive Solutions, Inc. (United States)

Published in SPIE Proceedings Vol. 1452:
Image Processing Algorithms and Techniques II
Mehmet Reha Civanlar; Sanjit K. Mitra; Robert J. Moorhead, Editor(s)

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