Handwritten Numerical Character Recognition Based on Paraconsistent Artificial Neural Networks

This paper presents an automated computational process able to recognize a handwritten numerical characters and Magnetic Ink Character Recognition used on bank checks based on Paraconsistent Artificial Neural Networks. The methodology employed was chosen for being a tool able to work with imprecise, inconsistent and paracomplete data without trivialization. The recognition process is performed from some character features previously selected based on some Graphology and Graphoscopy techniques and, the analysis of such features as well as the character recognition are performed by Paraconsistent Artificial Neural Networks.

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