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Algorithm Using Deep Learning for Recognition of Japanese Historical Characters in Photo Image of Historical Book

机译：利用深度学习识别历史书照片图像中日本历史人物的算法

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摘要

In Japan, there are vast amount of classical books written in cursive Japanese that cannot be read by modern people. It is difficult to recognize each cursive Japanese separately, because they are written connected. Furthermore, there are many types of shape of characters. Therefore, an efficient method to convert them into modern characters automatically is required. Some methods recognizing a block of a few characters using deep learning have been studied so far. However, every page in a Japanese historical book is stored by a photo image; therefore, it is desirable to recognize all characters in a photo image at once. In this paper, we propose a method using deep learning to recognize cursive Japanese in a photo image without separating a block of characters manually. Furthermore, we evaluate the performance of the proposed algorithm using photo images of an actual book.
机译：在日本，有大量的古典书籍用现代人无法阅读。很难分别识别每个粪便日语，因为它们是连接的。此外，有许多类型的字符形状。因此，需要一种有效的方法，可以自动将它们转换为现代字符。到目前为止，已经研究了一些使用深度学习的一些人物块的方法。但是，日本历史书中的每个页面都由照片图像存储;因此，期望一次识别照片图像中的所有角色。在本文中，我们提出了一种利用深度学习的方法，在不分离照片图像中识别卷发日语，而不手动分离字符块。此外，我们使用实际书的照片图像评估所提出的算法的性能。

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