A neural-net board system for machine vision applications

H. P. Graf, R. Janow, C. R. Nohl, J. Ben

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The authors describe a board system that integrates an analog neural net chip with a digital signal processor and fast memory. This system is in use as a coprocessor of a workstation where it accelerates computationally-intensive tasks for machine vision. A software environment has been developed to support image processing and testing of the system. The system was used to develop an application where the neural net determines the position and size of characters in complex images. For this task an increase in speed of a factor over 1000 over a workstation was achieved.

Original languageEnglish (US)
Title of host publicationProceedings. IJCNN-91-Seattle
Subtitle of host publicationInternational Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages481-486
Number of pages6
ISBN (Print)0780301641
StatePublished - 1991
Externally publishedYes
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: Jul 8 1991Jul 12 1991

Publication series

NameProceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period7/8/917/12/91

All Science Journal Classification (ASJC) codes

  • General Engineering

Fingerprint

Dive into the research topics of 'A neural-net board system for machine vision applications'. Together they form a unique fingerprint.

Cite this