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Proceedings Paper

Machine vision applications of analog neural net chips
Author(s): H. P. Graf; E. Sackinger; L. D. Jackel
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Paper Abstract

Two of our analog neural net chips have been integrated into board systems and are being used now in a variety of image recognition applications. One of the two circuits, the NET32K chip, has connections with a low resolution of between one and four bits. With this chip one can scan up to 32 kernels of a size of 16 X 16 pixels over an image. It is used mainly for extracting geometrical features from images, for such applications as image segmentation. The second of the chips, named ANNA, operates with a higher resolution of 6 bits in the weights and 3 bits in the states. It has been designed for implementing nets to recognize characters. The computation rates obtained with these circuits are 10 to 100 times faster than those of standard processors. With the NET32K chip we achieve between two and ten billion connections per second. With the ANNA chip we read over 150 characters per second, a tenfold increase compared with a digital signal processor.

Paper Details

Date Published: 16 September 1992
PDF: 9 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.139996
Show Author Affiliations
H. P. Graf, AT&T Bell Labs. (United States)
E. Sackinger, AT&T Bell Labs. (United States)
L. D. Jackel, AT&T Bell Labs. (United States)

Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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