An approach to industrial computer vision using syntactic/semantic learning techniques

Author

David Jerome Braunegg

Date of Award

8-1983

Degree Type

Thesis

Major

Electrical Engineering

Major Professor

R. C. Gonzalez

Committee Members

E. L. Hall, M. G. Thomason

Abstract

Syntactic and semantic approaches to object pattern recognition are discussed. A well-known grammatical inference technique for syntactic pattern recognition is augmented with semantic considerations. Experimental results which demonstrate the power of the combined approach to recognition are presented. Limitations encountered with this approach along with suggestions for further research are discussed.

Recommended Citation

Braunegg, David Jerome, "An approach to industrial computer vision using syntactic/semantic learning techniques. " Master's Thesis, University of Tennessee, 1983.
https://trace.tennessee.edu/utk_gradthes/14759