The recognition experiment on HCL2000, a handwritten Chinese character database, showed that our method improved the recognition precision of whole system.
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。
In order to improve the pattern recognition precision, using the neural network recognition and optimal method, a new pattern recognition method of shape signal was established.
为了提高带材板形识别的精度，应用神经网络和最优化方法，构建了一种新的板形信号模式识别方法。
Experiments show that the new algorithm has good recognition precision and realtime tracking performance, and can adapt to the application requirements of augmenting reality systems.
实验表明，识别算法具有较好的跟踪精度和实时性，能够满足增强现实系统的应用要求。
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