Data Mining Ancient Script Image Data Using Convolutional Neural Networks

Shruti Daggumati, P. Revesz
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引用次数: 20

Abstract

The recent surge in ancient scripts has resulted in huge image libraries of ancient texts. Data mining of the collected images enables the study of the evolution of these ancient scripts. In particular, the origin of the Indus Valley script is highly debated. We use convolutional neural networks to test which Phoenician alphabet letters and Brahmi symbols are closest to the Indus Valley script symbols. Surprisingly, our analysis shows that overall the Phoenician alphabet is much closer than the Brahmi script to the Indus Valley script symbols.
基于卷积神经网络的古文字图像数据挖掘
近年来,古代文字的激增催生了庞大的古代文本图像库。对收集到的图像进行数据挖掘,可以研究这些古代文字的演变。特别是,印度河流域文字的起源备受争议。我们使用卷积神经网络来测试哪些腓尼基字母和婆罗门符号最接近印度河流域的文字符号。令人惊讶的是,我们的分析表明,总的来说,腓尼基字母比婆罗门文字更接近印度河流域的文字符号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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