一款手写数字识别系统，不错哦！
目前，手写数字识别技术已被广泛应用。
Technology of handwritten Numbers recognition has been widely applied at present.
手写数字识别技术是近年来研究的热点。
Nowadays, handwritten digit recognition technique is researched importantly.
验证支持向量机用于手写数字识别的有效性。
Validating the effectiveness of support vector machine for handwritten digit recognition.
该文提出了一种基于主曲线的脱机手写数字识别方法。
The paper proposes a method of off-line handwritten digit recognition based on principal curves.
因此，研究简单高效的手写数字识别依然是一个重要的研究方向。
Therefore, the study of simple and efficient handwritten numeral recognition is still an important research direction.
手写数字识别和脱机手写汉字识别的实际应用验证了所提的理论和方法。
Practice in handwritten numeral recognition and off line handwritten Chinese character recognition strongly supports the ideas and the methods.
在图像分析处理中，FCM聚类算法可以有效地用于图像处理，特别是手写数字识别中。
In the image analysis, FCM clustering algorithm can be effectively used for image processing, especially for hand-written numeral recognition.
手写数字识别技术是近年来研究的热点，具有广泛的应用前景，同时也是一个非常具有挑战性的课题。
Handwritten numeral recognition technology is a research hotspot in recent years, it has wide applications, but it is also a very challenging subject.
手写数字识别技术是近年来研究的热点，具有广泛的应用前景，同时也是一个非常具有挑战性的课题。
Handwritten numeral recognition belongs to the field of pattern recognition, which is a hot field for a large number of researchers and also is a critical step in entry of information.
说明：自己编写的一个关于MISNT手写数字识别的源程序，是一种对原svm的改进算法，效果不错。
I have written about MISNT handwritten numeral recognition of the source, is an improvement on the original SVM algorithm, the effect is good.
为了提高手写数字识别的精度，本文将支持向量机应用于手写数字识别，开发了SVM-HDR软件系统。
To improve the accuracy of handwritten digit recognition, this paper applies support vectormachine to handwritten digit recognition and exploits a software system named SVM-HDR.
介绍了基于TMS320VC5402的手写数字识别系统和该系统的基本原理，给出了它的硬件原理图和软件设计程序框图。
This paper introduces a handwritten digit recognition system based on TMS320VC5402. The work principle is presented and the block diagram of hardware and program flow chart are given .
将BP神经网络引入到手写数字识别中，并采用多种输入模式对不同的BP网络进行训练，从而达到全面反映数字特征的目的。
BP neural network arithmetic is used in the handwritten numeral recognition system. In order to reflect the whole character, we use many input modes to train the networks.
在CBCL人脸库和USPS手写数字识别的实验中，给出了该算法和SVM、SOM算法的实验对比结果，说明了该学习算法的有效性。
The experiment on CBCL face database and USPS handwritten digital database presents the comparison of this algorithm with SVM and SOM, which illustrates the effectiveness of this learning algorithm.
该系统利用的是手写数字而非字母，这是因为别人或许能认出你的手写单词，却未必能轻易地识别出你手写的数字。
The system works using handwritten numbers instead of letters because although others may be able to recognize your penned words, they're not so good at distinguishing your handwritten numerals.
认证时，该程序给各参与者显示出一连串由五位数字组成的手写个人身份识别码，每个识别码都是从手写数字中随机抽取生成的。
At authentication, the program showed the participant a series of five-number handwritten PINs, each one randomly generated from the handwritten numerals.
我们通过解决一个具体的问题：交计算机识别手写数字，来学习神经网络与深度学习后面的核心理念。
We'll learn the core principles behind neural networks and deep learning by attacking a concrete problem: the problem of teaching a computer to recognize handwritten digits.
实验证明该方法有很高的识别率，能够有效地进行手写数字的分类，可以满足实际应用。
The result of experiment shows high recognition rate, which indicates that the method can effectively classify handwritten digits and be put into practical use.
最后，用子空间分类器和BP神经网络分类器构造了一个混联模型，用于手写英文字母和数字的识别。
A mix model with the subspace classifier and BP neural network classifier was realized, which is used in handwritten English letter and number recognition.
本文将二者结合起来，用小波变换抽取特征、用自适应共振art网络作模式分类器来识别手写数字。
This paper combines the two aspects to recognize handwritten digits by using wavelet transform to extract feature and Adaptive Resonance Theory (ART) Neural Networks for Classification.
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.
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.
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.
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.
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.
本文应用HMM概率模型和神经网络结合，对联机手写数字和数学符号进行识别。
We recognize on-line handwritten figure and some mathematic characters using the HMM neural networks, and achieve a better result.
最后在对手写数字进行识别时，先进行粗分类再进行细分类。
Finally coarse classification and precise classification are separately carried out in handwritten digits recognition.
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.
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.
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