Training system for neural networks

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395 22, 395 20, G06K 962

Patent

active

055726283

ABSTRACT:
In order for neural network technology to make useful determinations of the identity of letters and numbers that are processed in real time at a postal service sorting center, it is necessary for the neural network to "learn" to recognize accurately the many shapes and sizes in which each letter or number are formed on the address surface of the envelope by postal service users. It has been realized that accuracy in the recognition of many letters and numbers is not appreciably sacrificed if the neural network is instructed to identify those characteristics of each letter or number which are in the category "invariant." Then, rather than requiring the neural network to recognize all gradations of shape, location, size, etc. of the identified invariant characteristic, a generalized and bounded description of the invariant segments is used which requires far less inputting of sample data and less processing of information relating to an unknown letter or number.

REFERENCES:
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patent: 5067164 (1991-11-01), Denker et al.
patent: 5239594 (1993-08-01), Yoda
patent: 5251268 (1993-10-01), Colley et al.
patent: 5337371 (1994-08-01), Sato et al.
patent: 5479575 (1995-12-01), Yoda

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