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手写数字字符识别的神经网络方法-Handwritten Character Recognition neural network
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CUDA应用:在CUDA上实现神经网络,识别手写数字,the implementation of a neural network with CUDA. Neural Network for Recognition of Handwritten Digits
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MATLAB 神经网络用于数字识别源程序 手写数字识别,有图例,大家可以看看,MATLAB neural network to identify the source for digital handwritten numeral recognition, there are legends, we will look at
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基于神经网络的手写数字识别系统,字符识别-Neural Network Based Handwritten Digit Recognition System
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实现神经网络的bp识别手写数字。改程序师用MATLAB实现的,里面代码可以直接用-Bp neural network to achieve handwritten numeral recognition. Reform program to achieve the division to use MATLAB, which code can be directly used
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神经网络手写数字识别。配合美国MNIST标准手写数字字体库-Handwritten digit recognition neural network. With the U.S. standard of handwritten digital font library MNIST
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基于人工神经网络的图像识别方法研究。基于神经网络的人脸检测研究。基于特征融合与神经网络的手写体数字识别技基于遗传神经网络的手写体数字识别研究术研究。基于遗传优化的神经网络的银行票据手写数字识别。一种改进的人工神经网络模型-Based on artificial neural network image recognition method. Neural Network Based Face Detection Research. Based on Feature Fusion and Neur
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基于BP神经网络的手写签名识别方法。训练样本,识别签名-Based on BP Neural Network Recognition of handwritten signatures. Training samples to identify the signature
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手写体数字识别的VC实现
使用神经网络算法对手写体数字进行识别,训练后识别率可达90%左右。-Handwritten Digit Recognition of the VC to achieve the use of neural network algorithm for handwritten numeral recognition, training, recognition rate can reach about 90.
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图像模式识别的各种算法及其编程实现,包括模板匹配分类器、几何分类器和神经网络分类器等,可用于手写数字的识别。-A variety of image pattern recognition algorithm and its programming, including template matching classifier, geometric classifier and neural network classifiers, etc., can be used for handwritte
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针对10个手写数字的识别问题,设计了一个BP神经网络,使它能够正确识别10个数字。-Against the 10 handwritten numeral recognition problem, a BP neural network is designed so that it can correctly identify the 10 digits.
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图象处理 模式识别 多种分类方法(最临近匹配分类器、Bayes分类器、线性函数分类、非线性函数分类、神经网络分类)识别0-9数字 手写数字与数字图片,包括设计训练样品库、可以选择多种分类器来识别识别0-9这十个阿拉伯数字,包括临时手写的数字,也包括图片中的数字
-Pattern recognition image processing a variety of classification (the most close to matching classifier, Bay
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采用神经网络实现手写识别的一种方法,建立Bp神经网络,采用快速训练方法,可快速完成一类相关手写字体的模式识别,识别率较高,当字体变化较大识别率降低时,可重新训练具有较强的适应性。实验证实本方法较好实现了手写字符识别,但也存在识别速度较慢,有时训练不收敛等缺点-Handwriting recognition using neural network is a way to establish Bp neural network, using fast training methods, and c
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用BP神经网络进行手写数字的识别,特征提取是基于统计模式识别的方法-BP neural network with the handwritten numeral recognition, feature extraction is based on statistical pattern recognition approach
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采用BP神经网络对手写体数字进行识别。识别相当方便有效快捷-Using BP neural network to recognize handwritten digits. Very easy to identify effective and efficient
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利用小波和RBF神经网络进行手写数字识别-Wavelet and RBF neural network handwritten numeral recognition
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基于MATLAB并利用神经网络实现对手写数字0-9十个数字的识别代码-based on MATLAB and recognition of handwritten digits 0-9 it is mean to design a simple handwritten numeral recognition system using neural network.
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基于样条权函数神经网络的手写系统实现。验证了样条权函数神经系统在手写数字识别中的应用价值。-Function neural network system to achieve spline right hand. Verify that the spline weight function of the nervous system applications in handwritten digits recognition.
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利用基于概率的神经网络识别算法,进行手写字体的识别。-By using the neural network recognition algorithm based on probability,recognition of handwritten font.
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实现的一个用于手写数字识别的框架,可以设置神经网络结构,用的数据是mnist的(Implementation of a handwritten numeral recognition framework, you can set the neural network structure, the training data is MNIST)
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