Pattern recognition, similarity, neural nets, and optics

Henri H. Arsenault

doi:10.1117/12.34760

1 July 1990 Pattern recognition, similarity, neural nets, and optics

Henri H. Arsenault

Proceedings Volume 1319, Optics in Complex Systems; (1990) https://doi.org/10.1117/12.34760
Event: 15th International Optics in Complex Systems, 1990, Garmisch, Germany

Abstract

The arbitrary nature of similarity and invariance is examined and its implications for pattern recognition and classification are examined. Various measures of similarity are discussed and techniques for achieving invariance under translation rotation contrast and energy are briefly reviewed. We show how both matched filters and neural nets can achieve c!assification of objects into arbitrary classes. For neural nets different kinds of similarity measures can cause patho!ogica! behavior that can be avoided by using a specific normalized kind of similarity measure. Implications for unsupervised learning in certain kinds of neural networks !ike the are discussed.

Citation Download Citation

Henri H. Arsenault "Pattern recognition, similarity, neural nets, and optics", Proc. SPIE 1319, Optics in Complex Systems, (1 July 1990); https://doi.org/10.1117/12.34760

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