Application of feedforward neural networks to object recognition for image analysis

V. G. Sigillito, J. Sadowsky, I. N. Bankman, P. Willson

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

Abstract

Summary form only given, as follows. The automated analysis of X-ray images of mechanical fuses for nondestructive evaluation (NDE) requires that objects within the images be detected and recognized and that the orientations and relative positions of these objects be computed. Neural-network-based adaptive spatial filters for performing these functions are advantageous for many reasons, including robustness, flexibility, and adaptability to changes in fuse design. A research project has been started to investigate the use of feedforward neural networks to improve the performance of an NDE image analysis system. In particular, the objective was to develop a system which learns the rules for image understanding and could be applied to new or modified fuse designs with a minimum of software modification.

Original languageEnglish (US)
Title of host publicationProceedings. IJCNN - International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Number of pages1
ISBN (Print)0780301641
StatePublished - Jan 1 1992
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: Jul 8 1991Jul 12 1991

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Other

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

ASJC Scopus subject areas

  • Engineering(all)

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