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BP神经网络手写识别源代码，可进行手写数字识别功能-BP neural network source code, handwriting recognition, handwritten numeral recognition can be
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BP神经网络的手写数字识别 识别数字为0~-BP neural network recognition of handwritten numeral recognition numbers from 0 to 99
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基于BP神经网络的手写英文字母识别,使用C#语言编写，含字母图片-Based on BP neural network Handwritten English letters recognition, the use of C# language, including alphabet picture
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采用神经网络方法进行手写数字识别，包括特征提取和识别-
Using the neural network method for handwritten numeral recognition, including feature extraction and recognition
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handwritten character recognition using back propagation neural network
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RECOGNITION OF HANDWRITTEN ARABIC AND LATIN DIGITS WITH ARTIFICIAL
NEURAL NETWORK
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基于BP神经网络的手写数字识别系统，基于Matlab开发，实现手写输入板功能，特征提取，模型训练，手写识别等功能。详细使用方法在readme说明文档中。-Handwritten numeral recognition system based on BP neural network, developed based on Matlab, handwriting input board, feature extraction, model training, handwriting recogn
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BP神经网络，是运用人工智能的方法，训练权值，建立模式识别的模型。本程序源码，使用三层神经网络，，对隐层的节点个数使用经验公式，对其他的参数设置也进行了优化，实现了手写数字的识别， 可直接使用。
-BP neural network, the use of artificial intelligence methods, training weights to establish the model of pattern recognition. The program source cod
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手写体数字识别的Visual C实现使用神经网络算算法对手写体数字进行识别，训练后识别率可达90％左右。
-Handwritten numeral recognition, Visual C Neural Network Algorithm for recognition of handwritten digit recognition rate after training up to about 90 .
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基于BP网络的手写大写字母识别，能较好识别大写字母-Handwritten letter recognition based on BP neural network, to better identify the capital letters
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VC++实现多种方法的手写数字识别 可直接运行 如BP神经网络等 ，经测试可直接使用。
-Handwritten numeral recognition VC++ to achieve a variety of methods can be run directly such as BP neural network has been tested and can be used directly.
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基于BP神经网络的手写体数字识别中用到的特征提取工具。-Extraction tool based on the characteristics used in the BP neural network handwritten digit recognition.
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在VC++6.0环境下运行.手写数字的分类识别，并有详细的程序使用方法。分别采用模板匹配分类器，Bayes分类器，线性函数分类法，非线性分类，神经网络分类器进行识别，功能强大，还可以对比各种算法的优劣。-VC++6.0 environment run. Classification and recognition of handwritten digits, and a detailed program to use. Template matching classifier Bayes cla
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采用C++语言编写的基于BP神经网络的手写体数字识别程序，使用方式为通过命令提示符向main函数传递待识别的图像的绝对路径。-Using C++ language through the command prompt is passed to the main function to be identified image handwritten digit recognition based on BP neural network program, use absolute paths.
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Towards Neural Network Recognition
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Handwritten Arabic Letters
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基于神经网络的手写体数字识别，它是用matlab实现的，其中用3种不同的神经的网络方法实现了手写体数字的识别，非常利于初学者的学习和交流。-Handwritten digit recognition based on neural networks, which is achieved using matlab, in which three different neural network to achieve the recognition of handwritten digits, is
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手写数字的识别的matlab实现，运用基本的图像处理和BP神经网络来实现，程序的使用方法请参阅 readme.txt-Handwritten digit recognition matlab realize, the use of basic image processing and BP neural network to achieve the program' s usage, please refer to the readme.txt
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采用典型的BP算法实现了基于MNIST的手写数字识别采用输入层、隐含层和输出层的三层结构，实现了BP算法下的神经网络。用7000个样本进行自洽检验，正确率99.79 。-Using typical BP algorithm based on MNIST handwritten numeral recognition using input layer, hidden layer and output layer, three-layer structure, to achieve the neu
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This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot
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MFC实现手写数字的识别，包含Beyes分类，线性函数分类，神经网络分类等各种算法的实现-MFC to achieve recognition of handwritten digits, including Beyes classification to achieve a linear function of classification, neural network classification of various algorithms
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