Machine vision applications of analog neural net chips

H. P. Graf; E. Sackinger; L. D. Jackel

doi:10.1117/12.139996

16 September 1992 Machine vision applications of analog neural net chips

H. P. Graf, E. Sackinger, L. D. Jackel

Proceedings Volume 1709, Applications of Artificial Neural Networks III; (1992) https://doi.org/10.1117/12.139996
Event: Aerospace Sensing, 1992, Orlando, FL, United States

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.

Citation Download Citation

H. P. Graf, E. Sackinger, and L. D. Jackel "Machine vision applications of analog neural net chips", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.139996

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