3 May 1988 Adaptive Learning Optical Symbolic Processor
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Proceedings Volume 0882, Neural Network Models for Optical Computing; (1988) https://doi.org/10.1117/12.944098
Event: 1988 Los Angeles Symposium: O-E/LASE '88, 1988, Los Angeles, CA, United States
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.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Casasent, Abhijit Mahalanobis, "Adaptive Learning Optical Symbolic Processor", Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944098; https://doi.org/10.1117/12.944098
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