Proceedings Paper
Generalized neocognitron model for facial recognition| Format | Member Price | Non-Member Price |
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Paper Abstract
The Fukushima's neocognitron model is generalized to a parallel neocognitron architecture which is applied for gray-scale facial recognition. Experiments show that the system can recognize human faces after learning. Results using the single neocognitron model for facial recognition or other gray-scale image recognition problems are not satisfactory.
Paper Details
Date Published: 1 October 1991
PDF: 11 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48401
Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)
PDF: 11 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48401
Show Author Affiliations
Su-Shing Chen, Univ. of North Carolina/Charlotte (United States)
Young-Sik Hong, Dongguk Univ. (South Korea)
Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)
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