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相关概念视频

Bone Markings01:26

Bone Markings

5.1K
Bones have various surface features that help form joints and attach to other soft tissues. Depending on the function, bone markings are categorized into articulating projections, processes for attachment, depressions, and openings.
Articulating Projections
Articulating projections are found where two bones meet to form a joint. These structures are usually found at the ends of bones. The largest articulation is a rounded projection called the head, supported by a narrow neck at the ends of...
5.1K

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Optimized Bone Sampling Protocols for the Retrieval of Ancient DNA from Archaeological Remains
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一个开放的数据集,用于预言骨字符识别和破译.

Pengjie Wang1, Kaile Zhang1, Xinyu Wang2

  • 1Huazhong University of Science and Technology, Wuhan, 430074, China.

Scientific data
|September 6, 2024
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概括

研究人员创建了HUST-OBC数据集,以帮助破译古代中国的Oracle Bone Script (OBC). 这一大数据集包含超过14万张图像,旨在克服理解朝文本的挑战.

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科学领域:

  • 数字人文学科 数字人文学科
  • 人工智能的人工智能
  • 考古学的考古学

背景情况:

  • 语骨文字 (OBC) 是一个重要的早期中国文字系统,起源于王朝 (大约3000年前).
  • 解读OBC对于理解中国古代历史和文化至关重要,但由于文本退化而具有挑战性.
  • 人工智能 (AI) 提供了OBC解密的潜力,但缺乏足够高质量的数据集.

研究的目的:

  • 介绍HUST-OBC数据集,这是人工智能驱动的OBC解密的全面资源.
  • 促进对中国古代文字和王朝研究的研究.

主要方法:

  • 从各种来源编制一个大规模的数据集 (HUST-OBC).
  • 包括140,053张图像:1,588个破译字符中的77,064个和9,411个未破译字符中的62,989个.
  • 将所有相关代码和数据集公开提供.

主要成果:

  • 创建了HUST-OBC数据集,其中包含大量解密和未解密的Oracle骨头字符.
  • 该数据集为开发和培训用于古代脚本分析的AI模型提供了基础.

结论:

  • HUST-OBC数据集解决了在人工智能辅助的OBC研究中对高质量的数据的关键需求.
  • 预计这项资源将大大促进古代中国文字的破译和相关的历史研究.