搜索资源列表
Demo-Mnist
- 基于神经网络的手写数字识别的源代码，绝对能够正常编译并运行！-based on neural network handwritten numeral recognition of the source code is absolutely normal to compile and run!
Demo-Mnist
- 基于神经网络的手写数字识别的源代码，绝对能够正常编译并运行！-based on neural network handwritten numeral recognition of the source code is absolutely normal to compile and run!
matlab_read_idx-ubyte
- 做手写阿拉伯字体识别时候需要用到图像数据文件。这时可以从http://yann.lecun.com/exdb/mnist/网站上下载数据源文件。这个程序可以很方便地将源文件读到matlab工作区间中去。-Arab make handwriting fonts needed to identify when the image data files. At this time http://yann.lecun.com/exdb/mnis
nnpractice
- 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
MNIST-handwritten-digits
- 手写数字识别数据集，MNIST，包括原始数据集的所有样本，以及抽取的2000个样本的子集，.mat格式。美国著名数据集NIST的子集，模式识别常用实验数据集-handwritten digits recognition ,dataset, MNIST from NIST, .mat file,
MNIST_theano
- 利用theano库完成MNIST手写识别，包括稀疏自编码机，多层感知机，卷积神经网络-using the theano to complete the handwriting congnization in MNIST ,include Denoising AutoEncoder,MLP,Convolution Neutral Network.
MNIST(tensorflow)
- 基于tensorflow的手写识别，训练后可以识别手写数字-Based on tensorflow handwriting recognition, training can identify handwritten numbers
readMNIST
- 用ELM实现手写数字的识别，快速，用MNIST数据库(Handwritten numbers recognition realized by ELM)
HandWriteOCR
- 手写汉字识别程序，包含训练和检测两部分，基于mnist库做训练和测试(Handwritten Chinese character recognition program, including training and testing of two parts)
codecnnMNIST
- 用cnn卷积神经网络实现对mnist手写库的识别(mnist classfication with convolution neural network)
MNIST
- 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
MNIST
- 简单的手写数字识别，在深度神经网络中的简单尝试，对于初学者有个很好的理解(Simple handwritten numeral recognition, in the depth of neural network simple attempt, for beginners have a good understanding)
mnist1
- 训练手写数字识别算法，正确率达到91.6%(Training handwritten numeral recognition)
神经网络mnist
- 利用神经网络对手写识别系统进行分类，正确率高达92%。(Using neural network to classify handwritten recognition system, the correct rate is as high as 92%.)
mnist
- 深度学习时间手写数字识别，使用python和tensorflow实现(Handwritten numerals recognition in depth learning time)
chinese_test
- 手写汉字识别，数据集训练，MNIST，Deep Convolutional Network识别手写汉字(Handwritten Chinese character recognition, data set training, MNIST, Deep Convolutional Network)
LeNet
- tensorflow实现手写体识别（包含mnist数据集）(Handwritten recognition by tensorflow)
my_cnn.tar
- 用卷积神经网络实现手写数字识别，数据集为mnist数据集(Convolution neural network is used to realize handwritten numeral recognition. Data set is MNIST data set.)
手写MNISTmatlab实现
- 资料可以直接运行，是matlab源码，实现了AI领域常见的手写字符MNIST数据集的识别，一般都是python做，matlab实现的很少，就算有也经常报错，因此这里是提供了例程以及数据集！数据集也是matlab能直接读取的MNIST格式！下载这个资料连数据集都不用单独下载了，节省时间。(The data can be run directly. It is the source code of MATLAB. It realizes t
BP_mnist_UI-master
- 基于BP神经网络的手写数字识别，有完整代码(based image segmentation algorithm)