Artificial Neural Networks and Fuzzy Logic for Recognizing Alphabet Characters and Mathematical Symbols

机译：人工神经网络和模糊逻辑识别字母字符和数学符号

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摘要

Optical Character Recognition software (OCR) are important tools for obtaining accessible texts. We propose the use of artificial neural networks (ANN) in order to develop pattern recognition algorithms capable of recognizing both normal texts and formulae. We present an original improvement of the backpropagation algorithm. Moreover, we describe a novel image segmentation algorithm that exploits fuzzy logic for separating touching characters.

机译：光学字符识别软件（OCR）是获取可访问文本的重要工具。我们提出使用人工神经网络（ANN）来开发能够识别正常文本和公式的模式识别算法。我们提出了反向传播算法的原始改进。此外，我们描述了一种新颖的图像分割算法，该算法利用模糊逻辑来分离触摸字符。

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《International conference on computers helping people with special needs》|2016年|7-14|共8页
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Giuseppe Airo Farulla; Tiziana Armano; Anna Capietto; Nadir Murru; Rosaria Rossini;
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Artificial neural networks; Fuzzy logic; Kalman filter; Optical character recognition;

机译：人工神经网络;模糊逻辑;卡尔曼滤波器光学字符识别;

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Artificial Neural Networks and Fuzzy Logic for Recognizing Alphabet Characters and Mathematical Symbols

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