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1下载:
数字音效处理器以MATLAB为设计平台,有.wav文件的获取、滤波、保存和播放功能。在对声音文件进行基本波形分析和频率分析的基础上,增加了特殊音效的功能,并有8段均衡器可对声音信号进行调节后保存播放。此外还附有语音识别程序。-Digital audio processor uses MATLAB design platform,it has wav file access, filtering, saving and playback function. On the basis of soun
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数字识别,提供训练好的HOG分类器,对单个手写数字进行识别-Digital recognition, to provide a good training HOG classifier, for a single handwritten numeral recognition
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基于VS2010开发的数字辨识软件,采用BP神经网络算法,内附使用说明。-Digital recognition software developed based on VS2010, using BP neural network algorithm, containing instructions for use.
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利用神经网络进行手写数字识别演示代码!非常具有代表性!-Using neural network Digital Recognition demo code!
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BP神经网络,用于手写数字的识别,非常实用,可以直接运行。-The BP neural network to handwritten digital recognition, very practical, can be directly run.
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数字图像处理,基于BP神经网络识别手写数字-Digital image processing, BP neural network based recognition of handwritten numbers
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学习ALIENTEK手写识别库的使用,实现一个简单的数字/字符手写识别程序.-Learn to use ALIENTEK handwriting recognition library implements a simple digital/character handwriting recognition program.
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离散Hopfield神经网络的联想记忆——数字识别-
Associative memory of discrete Hopfield neural network Digital Recognition
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VC++ 手写文字识别程序源码。实现手写数字给出不同的分类器识别结果,可心采用模板匹配分类器(最邻近模板匹配法)识别。手写数字或者打开已有的手写数字图像后,在右视图空白处,单击鼠标左键,激活右视图,选择菜单中的各种分类算法,可以对手写数字进行分类。-VC++ handwriting recognition program source code. Handwritten numbers give different classification recognition result satisf
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载入数字车牌,智能识别,检测返回识别的数字,此外,也可以单独对打开的图片一步一步进行图像预处理工作,但要注意,每一步工作只能执行一遍,而且要按顺序执行。
“256色位图转为灰度图”-“灰度图二值化”-“去噪”-“倾斜校正”-“分割”-“标准化尺寸”-“紧缩重排”。采用神经网络进行训练识别,识别率达到90 -Loading digital license plate, identification, detection returns the identification number, is
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本案例描述了图像中手写阿拉伯数字的识别过程,对手写数字识别的基于统计的方法进行简要介绍和分析,并通过开发一个小型的手写体数字识别系统来进行实验。手写体数字识别系统需要实现手写数字图像的读取功能、特征提取功能、数字的模板特征库的建立功能及识别功能-This case describes the image recognition process handwritten Arabic numerals, a brief descr iption and analysis of the handwri
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实现数字卡片识别功能,效果非常好,可以准确识别0-9这10个数字-Digital card recognition function, the effect is very good, you can accurately identify the 10 digits 0-9
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一个案例,离散Hopfield神经网络的联想记忆—数字识别-Associative memory digital recognition of discrete Hopfield neural networks
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用卷积神经网络实现的手写数字识别(minst),可直接运行,识别率较高。用Tensorflow实现-Handwritten digital recognition (minst) with convolution neural network can be run directly and the recognition rate is high. Implemented with Tensorflow
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数字识别,特别好的数字识别方法,模板匹配算法-Digital recognition, particularly good digital recognition methods, and template matching algorithms
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用java编写的手写体数字识别,采用knn方法,识别的训练和测试对象来自mnist数据库的数据,已经将解压后文件放进去了,算法包括文件的读取,测试部分还有识别算法。 -Written by java handwriting digital recognition, using knn method to identify the training and test objects the mnist data, has been extracted after the file into t
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手写体数字识别的程序,用了三种方法,贝叶斯,最近邻和BP神经网络,用MATLAB编写的,算法简单易懂,结构清晰-Handwritten digital recognition procedures, using three methods, Bayesian, Nearest Neighbor and BP neural network, written in MATLAB, the algorithm is easy to understand, clear structure
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关于编译原理中数字的识别,用的是上下文无关文法,不错的(About the compiling principle of digital recognition, USES the context-free grammar, good)
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MNIST手写体数字识别库及图片提取代码MNIST手写数字库识别实现摘要手写数字识别是模式识别的应用之一。文中介绍了手写数字的一些主要特征,并提出了截断次数特征并利用截断次数特征进行了实验(MNIST handwritten digital identification library and picture extraction code MNIST handwritten numeral library identification implementation summary Handwr
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MATLAB 神经网络用于数字识别源程序,不错的源码 很好用(MATLAB neural network used for digital recognition source, good source is in good condition)
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