Share Email Print

Proceedings Paper

Large-scale neural network model for multiclass pattern recognition
Author(s): Thomas Taiwei Lu; Freddie Shing-Hong Lin; Hung Chou; Andrew A. Kostrzewski; Jenkin C. Chen
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

This paper presents a large-scale neural network training model--a gray-scale interpattern association neural network model for feature extraction and fast training. A neural network based composite filter (NNCF) concept is proposed for neural network training of Fourier plane filters. The NNCF generation methods can selectively enhance features in the Fourier domain. The nonlinear combination of multiple filters through neural network training enables multi-class pattern recognition.

Paper Details

Date Published: 9 November 1993
PDF: 12 pages
Proc. SPIE 2026, Photonics for Processors, Neural Networks, and Memories, (9 November 1993); doi: 10.1117/12.163590
Show Author Affiliations
Thomas Taiwei Lu, Physical Optics Corp. (United States)
Freddie Shing-Hong Lin, Physical Optics Corp. (United States)
Hung Chou, Physical Optics Corp. (United States)
Andrew A. Kostrzewski, Physical Optics Corp. (United States)
Jenkin C. Chen, Physical Optics Corp. (United States)

Published in SPIE Proceedings Vol. 2026:
Photonics for Processors, Neural Networks, and Memories
Stephen T. Kowel; William J. Miceli; Joseph L. Horner; Bahram Javidi; Stephen T. Kowel; William J. Miceli, Editor(s)

© SPIE. Terms of Use
Back to Top