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Deep Learning and Lexical Analysis Combined Rubbing Character Recognition

机译:深度学习和词法分析相结合的摩擦字符识别

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Rubbings are among the oldest ancient literatures and presumably contain a lot of knowledge yet to be discovered. However, as of now, the recognition process of rubbing characters is now completely done manually. Such process, due to varying styles of characters, takes an enormous amount of effort, and can be done by a small number of specialists. Still, the aging process, which may damage characters or add noises, further increases the difficulty of recognition. In this paper, we propose a method by combining deep learning and lexical analysis for increasing the accuracy of rubbing character recognition. This work is currently in progress, and the experimentation uses rubbing character database developed by Kyoto University. In the experiment, we use a rubbing image for recognition, and the experimental results verify the effectiveness of the proposed method.
机译:拓本是最古老的古代文学之一,并且大概包含许多尚待发现的知识。但是,到目前为止,摩擦字符的识别过程现在已完全由人工完成。由于角色风格的变化,这种过程需要花费大量的精力,并且可以由少量的专家来完成。尽管如此,可能会损坏字符或增加噪音的老化过程进一步增加了识别的难度。在本文中,我们提出了一种将深度学习与词法分析相结合的方法,以提高摩擦字符识别的准确性。这项工作目前正在进行中,实验使用的是京都大学开发的摩擦字符数据库。在实验中,我们使用摩擦图像进行识别,实验结果证明了该方法的有效性。

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