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Machine Learning approaches for Nastaliq style Urdu handwritten recognition: A survey

机译:Nastaliq风格乌尔都语手写识别的机器学习方法:一项调查

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In day to day life handwriting is a mean of communication and recording the information regardless of the new technologies. The handwritten information is converted into digital form that is used as an input. Recognition is an attractive area of interest in research in recent years. There are good recognition system available for alphabetical and symbolic languages but for the language based on Arabic script like Urdu no such recognition system exist. The recognition is done either online or offline. For an online recognition system the input is taken through stylus or tablet whereas offline recognition is done by taking images through scanner. With the development in electronic tablets the movements of pen are captured accurately. Recognition of Urdu handwritten text is very complex task due to challenges in Urdu script. In this paper a survey is carried out on different Deep learning and statistical techniques for handwritten text recognition.
机译:不论新技术如何,手写都是日常交流和记录信息的一种手段。手写信息被转换为数字形式,用作输入。识别是近年来研究中的一个有吸引力的领域。有很好的识别系统可用于字母和符号语言,但是对于基于阿拉伯文字的语言(如乌尔都语),则不存在这种识别系统。识别可以在线或离线完成。对于在线识别系统,输入是通过手写笔或平板电脑获取的,而离线识别是通过扫描仪获取图像的。随着电子数位板的发展,可以精确地记录笔的运动。由于乌尔都语文字的挑战,识别乌尔都语手写文本是一项非常复杂的任务。本文针对手写文本识别的不同深度学习和统计技术进行了调查。

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