使用IMU传感器编写Punjabi字符的惯性测量数据集
AnchalPreet Sharma1, Harsh Kumar1, Lakhjeet Kaur1
1Department of Computer Science, Akal University, Bathinda, Punjab 151302, India.
Data in brief
|December 6, 2024
概括
这项研究开发了一种使用惯性测量单位 (IMU) 收集数据以识别手写的旁遮普语和英语字母的新方法. 该系统捕捉了各种不同的写作风格,以提高模式识别准确度.
科学领域:
- 模式识别 模式识别
- 人与计算机的交互
- 计算语言学 计算语言学
背景情况:
- 手写识别系统经常与语言和区域脚本变化作斗争.
- 现有的数据集可能无法充分捕捉各种写作风格的动态细微差别.
- 惯性测量单位 (IMU) 提供了一种新的方法来捕获细粒度的运动数据.
研究的目的:
- 引入一种方法来创建一个全面的数据集,用于手写的旁遮普字母识别.
- 为了利用IMU捕捉动态的手写运动模式.
- 通过结合不同的写作风格来提高字符识别的准确性.
主要方法:
- 开发了使用惯性测量单位 (IMU) 的数据收集方法.
- 记录了多个参与者的手写动作,以捕捉不同的旁遮普语写作风格.
- 利用IMU数据来追踪详细的动态手写动作.
主要成果:
- 创建了一个数据集,有效地捕捉了手写的旁遮普文字的细微差别.
- 初步结果显示,在印度背景下识别手写英语字母的潜力很大.
- 该方法通过利用动态运动数据,证明了字符识别准确度的提高.
结论:
- 开发的方法和数据集为旁遮普语手写识别提供了坚实的基础.
- 这种方法显示了跨语言字母表识别的前景,包括印度语境内的英语.
- 这项研究有助于为各种语言环境开发更具适应性的模式识别系统.
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