汉字识别中，以往的分类器设计都是以字为单位的“字分类器”。
In Chinese Character Recognition, the classifier was designed as word classifier whose classification unit is a word in the past.
应用字符的特征矩阵设计了一个手写体汉字的分类识别算法，取得了较好的效果。
A handwritten Chinese character classifying algorithm is designed based on the character feature matrix with the excellent classifying effect.
并利用训练后得到的网络作为分类器设计并实现了一种多级策略的汉字识别系统。
Finallly taking advantage of the trained network model as a classifier, we implemented a multi-level strategy Chinese character recognition system.
通过粗分类、特征提取、判别与反馈校正，以提高汉字图像识别适应性和识别准确率。
The coarse classification, characteristics pick-up, judgement and feedback are used in the machine to increase the recognition adaptability and accuracy.
提出的脱机手写体汉字识别系统主要研究特征提取和分类识别两个模块。
The proposed off-line handwritten Chinese character recognition system was composed of a feature extraction module and a recognition module.
使用该B-P神经网络作为汉字的分类器，可以大大提高车牌汉字的识别率。
These features are used to train a B-P neural network, it is a classifier and can improve greatly the recognition rate of Chinese characters.
用该方法对手写体汉字作分类识别，实验结果显示，较之其它几种方法，它有更高的正确识别率。
This method is applied to classify and recognize the handwriting Chinese characters, and the experimental results show that this method is superior to the other method in terms...
本文提出一种联机识别自然手写体汉字的多分类器集成模型。
In the paper, a new multiple classifiers integrated model of online recognizing natural handwritten Chinese character is presented.
然后对脱机手写体汉字识别中常用的分类器以及集成方法进行了认真的学习和总结。
Then makes a summary of various classifiers and ensemble methods commonly used in the off-line handwritten Chinese characters recognition.
最后，设计神经网络分类器对汉字，字母，数字进行训练和识别。
Finally, design the neural network classifiers in order to train and recognize the character, letters and licenses.
研究了在粗分类中汉字特征选择对汉字识别性能的影响，研究了不同特征进行组合后组合特征的识别性能。
Studied the influence which character features have on the classification rate, and the performance of the combined features.
在HCL2000数据库上进行的实验表明，该方法可有效提高汉字分类器的识别率。
The recognition experiment on HCL2000, a handwritten Chinese character database, showed that our method improved the recognition precision of whole system.
本文开发了古汉字图像分类识别系统，应用结果表明本系统具有较高的分类识别能力。
In this paper, the ancient Chinese character recognition image classification system is developed. The results show that the system has high classification ability.
本文开发了古汉字图像分类识别系统，应用结果表明本系统具有较高的分类识别能力。
In this paper, the ancient Chinese character recognition image classification system is developed. The results show that the system has high classification ability.
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