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!
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
- 这个压缩包，是一个手写数字识别库，世界上最权威的，美国邮政系统开发的，可以作为标准的数据集合使用测试分类器-This compression package, is a handwritten numeral recognition , the world' s most authoritative, the U.S. postal system developed can be used as a standard data s
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)
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)
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)
fisher
- 利用fisher方法实现手写体数字多分类识别，采用mnist数据集(simple program using fisher)
least_square
- 利用最小二乘法实现手写体数字识别，采用mnist数据集(simple program using least-square)
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.)
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.)
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 re
input_data
- mnist数据集的导入文件，官网上有可能进不去(def maybe_download(filename, work_directory): """Download the data from Yann's website, unless it's already here.""")
MNIST数据集
- 手写数字识别数据集的训练集和测试集，关于BP神经网络(Handwritten digit recognition data set)
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)