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脱机字符识别算法,包括手写数字识别之Fisher线性判别,手写数字识别之模板匹配法,数字识别之神经网络法,细化算法
-offline character recognition algorithms, including handwritten digital identification Fisher Linear Discriminant. Handwritten identification template matching, digital identification neura
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关于手写字符识别的m语言程序。包内附有供sample的字符图片。-handwritten character recognition on the m language program. Packet containing a sample of the characters for pictures.
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应用于模式分类中,用模式匹配方法对数据进行分类来获得对手写汉字识别的功能-Applied to pattern classification, the use of pattern-matching methods to classify the data to obtain the function of Handwritten Chinese Character Recognition
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A Matlab Implementation of Optical Character Recognition (OCR)
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三种神经网络方法用于手写体字符识别PNN、RBF、BP-Three kinds of neural networks for handwritten character recognition PNN, RBF, BP
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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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Handwritten Character recognition
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OCR手写文字识别源码。陨落雕(ThirdApple)的大作,识别率不错,手写输入识别后分别给出匹配率和匹配的字符 -OCR handwritten character recognition source. Fall Eagle (ThirdApple)' s masterpiece, the recognition rate is true that handwriting recognition is given after the match rate and match each
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包括手写文字识别的各个步骤,图像的预处理、裁剪、大小转换、人工神经网络训练和识别等等。-Handwritten character recognition, including the various steps, image preprocessing, cropping, size, conversion, training and recognition of artificial neural networks and so on.
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支持向量机的研究现已成为机器学习领域中的研究热点,其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则,在最小化样本点误差的同时,缩小模型泛化误差的上界,即最小化模型的结构风险,从而提高了模型的泛化能力,这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的,经过十几年的研究和发展,已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势,已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。- Support
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自己制作基于“欧氏距离的算法”来识别文字的相似性,从而来识别手写文字的程序,开发环境是matlab.需要讲手写的字加到字库才可以哦。-Produce their own based on the " Euclidean distance algorithm" to identify the similarity of the text, handwritten text in order to identify the procedures, the development e
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利用计算机自动识别字符的技术,是模式识别应用的一个重要领域。人们在生产和生活中,要处理大量的文字、报表和文本。为了减轻人们的劳动,提高处理效率,50年代开始探讨一般文字识别方法,并研制出光学字符识别器。60年代出现了采用磁性墨水和特殊字体的实用机器。60年代后期,出现了多种字体和手写体文字识别机,其识别精度和机器性能都基本上能满足要求。如用于信函分拣的手写体数字识别机和印刷体英文数字识别机。70年代主要研究文字识别的基本理论和研制高性能的文字识别机,并着重于汉字识别的研究。-The use of
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这次还是课后作业
做的是hopfield的手写体字符识别
识别率对库文件的1能达到90 -This is homework to do is hopfield handwritten character recognition recognition rate for a library file can reach 90
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基于CNNs的手写字符识别系统,载入MNIST手写字符数据库,通过训练提取特征,达到99 的识别率-Based on CNNs handwritten character recognition system, load MNIST handwritten character database, extract features through training, up to 99 recognition rate
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以MATLAB作为系统开发软件,利用图形用户界面(GUI)设计一手写数字识别系统,实现26个手写英文字符的识别功能-Handwritten character recognition
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用 卷积神经网络进行手写字符 识别,内含mnist训练集-Handwritten character recognition, containing mnist convolution neural network training set
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a good document about Neural networks and CHARACTER RECOGNITION Handwritten character Recognition: Training a Simple NN for classification using MATLAB
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手写体字符识别GUI代码 Handwritten character recognition GUI- Handwritten character recognition GUI
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Andrew Ng Cousera 机器学习课程神经网络手写字符识别,源代码以及说明文档(Andrew Ng Cousera 's Machine learning courses, Neural Network handwritten character recognition, source code and documentation)
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在anaconda+opencv+tensorflow平台下,利用简单的CNN卷积神经网络进行手写字符识别(Under the anaconda+opencv+tensorflow platform, we use simple CNN convolution neural network to handwritten character recognition.)
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