Parameter Estimation and the applications in handwriting character recognition of 2-D stationary HMMs were discussed in this paper.
本文讨论了二维平稳隐马氏模型参数估计及其在文字识别中的应用。
The proposed approach in this paper offers a great potential for solving difficult handwriting character recognition problems under reasonable assumptions.
本文用到的方法对于在合理的模型假设下解决手写字符识别问题呈现了很大的潜力。
The experiments show that the recognition accuracy of printing character is 95.5% and the recognition accuracy of handwriting character is 90.3%.
经实验表明，印刷体字符的识别准确率为95.5%，手写体字符的识别准确率为90.3%。
In the research of handwriting Chinese character recognition, no researcher raised a mathematical model of handwriting Chinese characters which is discussed in this paper.
在手写汉字识别的研究中，鲜有研究者提出建立手写汉字的数学模型，本文在这方面作了一些探讨。
Another research for application of neural networks is character recognition and handwriting recognition.
神经网络的另一个应用研究是字符识别和手写识别。
And for the handwriting character the system adopts BP neural network to realize the recognition.
而对于手写体字符，系统采用BP神经网络来实现字符的识别。
Proposed in this paper is a fast multi-stage classification strategy for large class sets, such as handwriting Chinese character recognition.
针对大类别集分类问题提出了一种新的快速分类方法。
This paper is focus on small set character recognition. Based on skeleton graphics, handwriting Chinese character is defined as a set of isolated branch, isolated loop and component. Relation…
本文针对小类别数手写汉字，在骨架图形的基础上，把手写汉字看作孤枝、孤环和部件的集合，并定义三者之间的方位关系，从而建立手写汉字的数学模型。
This paper is focus on small set character recognition. Based on skeleton graphics, handwriting Chinese character is defined as a set of isolated branch, isolated loop and component. Relation…
本文针对小类别数手写汉字，在骨架图形的基础上，把手写汉字看作孤枝、孤环和部件的集合，并定义三者之间的方位关系，从而建立手写汉字的数学模型。
应用推荐