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Updated: Jul 9, 2025

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Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
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一个在线的多语言数字数据集Devnagari和英语语言的模式识别研究的模式识别研究
Meenal K Jabde1, Chandrashekhar H Patil1, Amol D Vibhute2
1School of Computer Science, Dr. Vishwanath Karad MIT World Peace University, Pune, MH, India.
Data in brief
|November 29, 2023
概括
这项研究为德瓦纳加里语和英语引入了新的空中编写的数字数据集,解决了模式识别资源的缺口. 免费使用的2万张图像数据集有助于多语言手写分析.
科学领域:
- 计算机视觉 计算机视觉
- 模式识别 模式识别
- 多语言数据多语言数据
背景情况:
- 空气写字系统在医疗保健和金融等各个领域都有应用.
- 现有的空写数字数据集是有限的,特别是对于德瓦纳加里和英语脚本.
- 模式识别研究需要全面的多语言数值数据集.
研究的目的:
- 为德瓦纳加里语和英语引入新的,大规模的空写数字数据集.
- 制定一个系统的策略来收集多语言的空写数据.
- 为图案识别和手写分析提供一个有价值的资源.
主要方法:
- 提出并实施了一个系统的数据收集策略.
- 100名年龄在20-40岁之间的个人参与了数据收集.
- 每个参与者都在空中十次写出德瓦纳加里和英语数字0-9 .
主要成果:
- 创建了一个新型数据集,包括20,000个空中编写的数字图像 (10,000个德瓦纳格里,10,000个英语).
- 该数据集捕获实时空气写字模式,用于多语言数字识别.
- 该数据集为研究目的免费提供.
结论:
- 新创建的德瓦纳加里和英语空中编写的数字数据集填补了一个关键的研究缺口.
- 预计该资源将在多语言环境中推进模式识别和手写分析.
- 建议的数据收集方法可以适应其他脚本和字符.
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