手写体数字识别系统用于数据信息的采集。
Handwritten numeral Recognition System is used to obtain numeral information.
本文论述并设计实现了一个手写体数字识别系统。
This paper discusses how to design and develop a system for recognition of handwritten digits.
采用了一种基于笔道方向的手写体数字识别的方法。
The method of handwritten digit recognition based on written direction is adopted.
手写体数字识别问题是模式识别领域的一个重要研究课题。
The handwritten digital recognition is an important problem of pattern recognition field.
本文主要研究BP神经网络在脱机手写体数字识别方面的应用。
In this paper we give a kind of handwritten digits recognition method based on BP neural network.
将模糊特征提取技术与区组设计前馈网络相结合用于手写体数字识别。
Fuzzy feature extraction and block design feedforward networks are employed to recognize handwritten digits.
将经验模型分解方法应用于手写体数字识别，提出了一种新的识别方法。
This paper presents a novel method for handwritten numeral recognition based on empirical mode decomposition.
主要研究了手写体数字识别的特征提取方法，并提出了一种新的边界特征提取方法。
It proposes new boundary feature extraction way of handwritten numeral recognition, which is simple and effective.
主要研究了手写体数字识别的特征提取方法，并提出了一种新的边界特征提取方法。
The paper proposes a method of off-line handwritten digit recognition based on principal curves.
手写体数字识别网络的训练过程需耗费大量时间，训练时间的优化有着重要的意义。
For recognizing handwritten digits, the training process of the network to need to waste a great deal of time.
针对传统的数字识别方法的复杂性和局限性，提出了基于BP神经网络的手写体数字识别系统。
To counter the complexity and limitation of traditional digital distinguish methods, Script Digital Distinguish System based on BP Neural Network is proposed.
手写体数字识别是模式识别中的研究课题之一，本文对多层神经网络用于手写体数字识别进行了探讨。
One of the main study in pattern recognition is handwritten digit recognition, In thispatper, we discuss multi-layered neural network used to handwritten digit recognition.
本文建立了一个集成型神经网络手写体数字识别系统，系统主要由两部分构成，即：学习部分和识别部分。
In this paper, a handwritten digit recognition system based on integrated neural network is set up. The system was consisted of two parts: Learning part, recognition part.
用神经网络识别手写体数字，大多数采用的是单个的神经网络结构。
Most of the neural network handwritten digits recognition systems adopt a net - work with single structure.
通过测试，本识别系统对于较规范的手写体数字的识别达到了很好的识别效果。
Recognition system in this paper has achieved a good rate of recognition in random handwritten numeral by test.
提出了一种识别自由手写体数字的新方法。
A new recognition method for free handwritten Numbers is presented in the paper.
把这种动态组合方法具体应用到手写体数字的识别中，实验结果同样证实了它的可行性。
This method is applied in hand-written number recognition and experiment results also approve its feasibility.
介绍了在提取穿越次数特征、粗网格特征以及密度特征提取的基础上，应用SVM进行手写体阿拉伯数字识别的方法。
The paper introduces a script Arabic numerals recognition method applied SVM based on drawing out Traversing-times character and Wide-gridding character.
将这些壳系数输入前馈神经网络簇，以识别该手写体数字。
The shell coefficients are used as features to input into a feed-forward neural network to recognize the handwritten numerals.
提出一种基于二进小波变换与多层分组神经网络的自由手写体数字的多分辨率识别算法。
In this paper, a new scheme of multiresolution recognition of unconstrained handwritten numerals based on dyadic wavelet transform and multilayer cluster neural network is presented.
它们的输入功能局限于几个按键或数字键，或者像个人数字助理（PDA）手写体识别功能那样，输入数据要花很长时间，它们所拥有的工作处理能力和内存都较小。
Their input capabilities are limited to a few buttons or numbers, or entering data takes extra time, as happens with a personal digital assistant's (PDA) handwriting-recognition capabilities.
对于印刷体数字的识别率达到了100%，对于手写体数字的识别也达到了98%以上。
The rate is 100% to print digits, more than 98% to the handwritten digits.
对于印刷体数字的识别率达到了100%，对于手写体数字的识别也达到了98%以上。
The rate is 100% to print digits, more than 98% to the handwritten digits.
应用推荐