搜索资源列表
xxuffei-BPWangLuo-ShuZiShiBie-master
- 使用神经网络算法算法进行手写数字的识别功能(Recognition of handwritten numbers using support Vector Machine)
Simple-Handwritten-Numerel-Recogntion-master
- 使用SVM算法进行数字图像识别，使用的是手写数字的训练(The use of SVM algorithm for digital image recognition is the training of handwritten numerals)
ccatx
- 介绍一种新颖的联机手写英文识别解码算法,采用主笔画层次建立Beam Viterbi算法,()
卷积神经网络 - 副本
- 对LeNet-5的matlab实现，识别MINST手写数字集，压缩文件包含程序文件和训练、测试图片文件，程序可直接运行（版本matlab R2008a）(For the matlab implementation of LeNet-5, the MINST handwritten numeric set is identified. The uploaded file contains the program file and the training and test file. The pr
5-4 tensorboard visualization
- tensorflow手写数字识别学习，根据样本进行计算(learn TensorFlow with mnist)
figure_recognition
- 基于python3的利用神经网络进行的手写数字识别程序。(A handwritten numeric recognition program based on python3 based on Neural Network.)
stacking
- kaggle digitrecognizer MNIST by stacking some machine learning method, such like GBM(Gradient Boosting Method), LR, Extra Randomized Trees, Random Forest,KNN,etc.用stacking的方法实现手写数字识别MNIST。(kaggle digitrecognizer MNIST by stacking some machine learnin
mnist.pkl
- mnist数据集，用于手写数字识别的数据集，机器学习入门必备(mnist data,original data in http://yann.lecun.com/exdb/mnist/)
mnist
- 手写数字识别。通过各种数字图片进行机器识别，属于机器学习入门级别编程。(Handwritten digit recognition. The machine is recognized by various digital pictures, which belongs to the introduction level programming of machine learning.)
纯C-CNN
- 纯C深度学习库，里面包含MNIST手写数字识别数据集，编译就能训练和预测(Pure C depth learning library, which contains MNIST handwritten digital recognition data sets, compiling can be trained and predicted.)
63267975multipath_doppler
- 如果输出为“0”(即结果错误)，则把网络连接权值朝着减小综合输入加权值的方向调整，其目的在于使网络下次再遇到“A”模式输入时，减小犯同样错误的可能性。如此操作调整，当给网络轮番输入若干个手写字母“A”、“B”后，经过网络按以上学习方法进行若干次学习后，网络判断的正确率将大大提高。这说明网络对这两个模式的学习已经获得了成功，它已将这两个模式分布地记忆在网络的各个连接权值上。当网络再次遇到其中任何一个模式时，能够作出迅速、准确的判断和识别。一般说来，网络中所含的神经元个数越多，则它能记忆、识别的模式
cnn
- matlab卷积神经网络cnn，用于手写字体识别或者其他都可以(matlab cnn For handwritten font recognition or anything else)
chapter19
- 在MATLAB平台上的基于svm的手写数字体识别(Handwritten numeral recognition based on svm)
python-dbn-master
- 运用python语言，基于dbn的手写数字体识别(Handwritten numeral recognition based on dbn using python language)
neural_network.tar
- 用于识别手写的0~9，10个数字,使用的工具是matlab(used to identify handwritten number 0~9 ,ten digits)
KNN python
- 关于K近邻算法的简单实现和一些例子，其中包括手写数字的识别(Simple implementation of K nearest neighbor algorithm and some examples)
mnist
- 利用keras实现手写数字识别，使用CNN模型 全连接层+两个卷积层，最后Softmax分类器，识别率超过96%(Using keras to realize handwritten numeral recognition baesd on CNN model. One whole connection layer + two convolution layers, and a Softmax classifier. The recognition accuracy is over 96%
cnn
- vs的cnn程序，没有调用任何库。有两个卷积层，用minst手写库识别(Vs's CNN program, no library is called. There are two coiling layers that are identified by a MINST handwritten Library)
MNIST_CNN 代码及测试结果
- 只含一层卷积层的CNN也可以将手写数字识别的正确率达到99%(The CNN with only one convolutional layer can also get the correct rate of handwritten digit recognition up to 99%.)
code(BP_to_MNIST)
- 使用BP神经网络实现手写字符库MNIST的识别。(The recognition of handwritten character library MNIST is realized by using BP neural network.)