G - Physics – 06 – F
Patent
G - Physics
06
F
354/59
G06F 15/18 (2006.01) G06K 9/66 (2006.01) G06N 3/04 (2006.01)
Patent
CA 2032126
HIERARCHICAL CONSTRAINED AUTOMATIC LEARNING NETWORK FOR CHARACTER RECOGNITION Abstract Highly accurate, reliable optical character recognition is afforded by a hierarchically layered network having several layers of parallel constrained feature detection for localized feature extraction followed by several fully connected layers for dimensionality reduction. Character classification is also performed in the ultimate fully connected layer. Each layer of parallel constrained feature detection comprises a plurality of constrained feature maps and a corresponding plurality of kernels wherein a predetermined kernel is directly related to a single constrained feature map. Undersampling is performed from layer to layer.
Denker John S.
Howard Richard E.
Jackel Lawrence D.
Lecun Yann
American Telephone And Telegraph Company
Kirby Eades Gale Baker
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