Share Email Print

Proceedings Paper

Adaptive Learning Optical Symbolic Processor
Author(s): David Casasent; Abhijit Mahalanobis
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Partitioning of an object into N parts and the use of M filters with different output patterns are used to produce an NM digit symbolic encoding of the input object. The rule based system and techniques to update partitions of the object are emphasized in this paper. Three-dimensional aspect-invariant, shift-invariant and distortion-invariant pattern recognition data are considered and provided to demonstrate the usefulness of this technique for adaptive image processing.

Paper Details

Date Published: 3 May 1988
PDF: 13 pages
Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944098
Show Author Affiliations
David Casasent, Carnegie Mellon University (United States)
Abhijit Mahalanobis, Carnegie Mellon University (United States)

Published in SPIE Proceedings Vol. 0882:
Neural Network Models for Optical Computing
Ravindra A. Athale; Joel Davis, Editor(s)

© SPIE. Terms of Use
Back to Top