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针对实际项目采用了webservice进行搭建分布应用及多线程进行分布式并行开发应用。本项目主要针对图象学的图象处理对已存在的图象进行数字识别，本项目还利用BP神经网络（人工智能）技术进行识别应用，本项目采用OCR、体征、BP三种识别方法进行有效识别，识别效率达到98 -100 ，运行效率95ms/56ms/0.9ms。-Webservice used for the actual project to build distributed applications and multi-threa
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optical characterset recognition (OCR), done in c#.net using neural networks
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神经网络编程_源代码，很不错的，值得一看，识别率高达98 -neural network programming source code, very good, worth a visit, the recognition rate is up to 98
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BP neural network function fitting and pattern recognition, Achieve serial data acquisition, Modeling and simulation pwm rectifie.
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Raya Punuo Fu index using the formula, The commonly used digital signal modulation based on artificial neural network, You can achieve data classification and regression pattern recognition.
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基于bp神经网络的人脸识别系统，训练样本大概5000左右可以识别图片中是否有人脸(Face recognition system based on BP neural network)
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基于卷积神经网络的手写汉字识别_matlab版本_可以识别509类手写汉字(Based on the _ handwritten Chinese characters recognition _matlab version convolutional neural network can identify 509 kinds of handwritten Chinese characters)
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实现图像识别，基于小波变换实现图像特征提取，然后神经网络进行训练(The image recognition is realized, the image feature extraction is realized based on wavelet transform, and then the neural network is trained.)
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