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A Medical Knowledge Based Postprocessing Approach for Doctor's Handwriting Recognition

机译:基于医学知识的医生手写识别的后处理方法

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In this paper, we propose a novel post processing approach for on-line handwriting recognition. Differing from the existing linguistic knowledge-based methods, we make use of domain specific knowledge to improve the performance of recognition. Our system recognizes doctor’s handwriting which often poses great challenges in readability, and then enhances the quality of recognized text by analyzing and restoring the text with a medical knowledge model. We show experiments with this approach on a set of medical handwriting data provided by the doctor, and the results are promising.
机译:在本文中,我们提出了一种用于在线手写识别的新型后处理方法。与现有的语言知识的方法不同,我们利用域特定知识来提高识别的表现。我们的系统识别医生的笔迹,这些笔迹通常会在可读性中提出巨大挑战,然后通过分析和恢复具有医学知识模型的文本来增强所公认的文本的质量。我们在医生提供的一套医疗笔迹数据上显示了这种方法的实验,结果是有前途的。

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