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Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
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古代的文字手写样本库.

Xiaojuan Liu1, Xu Han2, Shanxiong Chen3

  • 1School of Artificial Intelligence, Chongqing University of Technology, Chongqing, 400054, China.

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此摘要是机器生成的。

这项研究介绍了古代文字手写的大量数据集,对于开发用于识别和生成历史脚本的AI模型至关重要. 这些发现凸显了脚本的复杂性和数字保存的潜力.

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科学领域:

  • 历史语言学 历史语言学
  • 计算机视觉 计算机视觉
  • 数字人文学科 数字人文学科

背景情况:

  • 古代的文字是世界上六个最古老的书写系统之一,有8000年的历史.
  • 现有的研究缺乏全面的数据集,用于对古代脚本进行计算分析.

研究的目的:

  • 创建一个大规模的,注释的数据集,古代的文字手写.
  • 为了评估深度学习模型的古代文字识别.

主要方法:

  • 收集了来自310个人的427,939个手写的字符.
  • 从250个个人收集了连续的手写文本样本.
  • 开发了一种用于手写脚本的自动取样,切割和标签方法.

主要成果:

  • 数据集包括各种形状结构和古代Yi字符的写作风格.
  • 深度学习模型在数据集上显示了不同的识别性能.
  • 该数据集作为手写文本识别和生成的基准.

结论:

  • 开发的数据集对于推动古代文字识别和数字保存的研究非常有价值.
  • 古代易文字的复杂性为AI开发提供了独特的挑战和机会.