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SYSTEM AND METHOD OF CHARACTER RECOGNITION USING FULLY CONVOLUTIONAL NEURAL NETWORKS

机译:基于全卷积神经网络的字符识别系统及方法

摘要

Embodiments of the present disclosure include a method for extracting symbols from a digitized object. The method includes processing the word block against a dictionary. The method includes comparing the word block against a word in the dictionary, the comparison providing a confidence factor. The method includes outputting a prediction equal to the word when the confidence factor is greater than a predetermined threshold. The method includes evaluating properties of the word block when the confidence factor is less than the predetermined threshold. The method includes predicting a value of the word block based on the properties of the word block. The method further includes determining an error rate for the predicted value of the word block. The method includes outputting a value for the word block, the output equal to a calculated value corresponding to a value of the word block having the lowest error rate.
机译:本公开的实施例包括一种用于从数字化对象中提取符号的方法。该方法包括针对字典来处理单词块。该方法包括将单词块与词典中的单词进行比较,该比较提供置信度。该方法包括当置信度大于预定阈值时输出等于单词的预测。该方法包括当置信度小于预定阈值时评估字块的属性。该方法包括基于单词块的属性来预测单词块的值。该方法还包括确定该字块的预测值的错误率。该方法包括输出用于字块的值,该输出等于与具有最低错误率的字块的值相对应的计算值。

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