手写识别的研究进展

Seong-Whan Lee
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引用次数: 44

摘要

在线手写识别采用离散隐马尔可夫模型,快速学习变音符处理,使用有效的会计程序进行前向搜索,结合了不同分类器和知识水平的手写形式阅读器架构,这是手写文本识别系统自适应识别系统架构的第一步,用于识别不带世界分割的草书短语的搜索算法,用于确定人类阅读中使用的特征的方法一种基于形状矩阵和hmm相结合的最大后验概率估计的手写体识别文档理解的高级分割技术,用于手写象形文字识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in Handwriting Recognition
On-line handwriting recognition by discrete HMM with fast learning diacritical processing using efficient accounting procedures in a forward search a handwritten form reader architecture combining different classifiers and levels of knowledge - a first step towards an adaptive recognition system architecture for handwritten text recognition systems search algorithms for the recognition of cursive phrases without world segmentation a method for the determination of features used in human reading of cursive handwriting global methods for stroke segmentation an advanced segmentation technique for cursive word recognition document understanding based on maximum a posteriori probability estimation combining shape matrices and HMMs for hand-drawn pictogram recognition.
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