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摘要翻译：
即使在二十一世纪的今天，手写通信也有自己的立足之地，在日常生活中，手写通信在全球范围内被用作通信手段，记录着与他人分享的信息。手写体字符识别的挑战在于手写体字符的变异和变形，因为不同的人可能会使用不同的笔迹风格，以及绘制相同形状的手写体字符的方向。本文阐述了手写体字符的本质，手写体数据向电子数据的转换，以及用神经网络方法使机器能够识别手写体字符。
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英文标题：
《Machine Recognition of Hand Written Characters using Neural Networks》
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作者：
Yusuf Perwej, Ashish Chaturvedi
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最新提交年份：
2012
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
Even today in Twenty First Century Handwritten communication has its own stand and most of the times, in daily life it is globally using as means of communication and recording the information like to be shared with others. Challenges in handwritten characters recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwriting, and direction to draw the same shape of the characters of their known script. This paper demonstrates the nature of handwritten characters, conversion of handwritten data into electronic data, and the neural network approach to make machine capable of recognizing hand written characters.
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PDF链接：
https://arxiv.org/pdf/1205.3964
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