文件名称:CNN

  • 所属分类:
  • 其他小程序
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2016-03-30
  • 文件大小:
  • 14.06mb
  • 下载次数:
  • 0次
  • 提 供 者:
  • 刘**
  • 相关连接:
  • 下载说明:
  • 别用迅雷下载,失败请重下,重下不扣分!

介绍说明--下载内容均来自于网络,请自行研究使用

这是个卷积神经网络的实现代码,对手写体进行识别,现在正确率可以达到90 -This is a convolution neural network implementation code of conduct handwriting recognition accuracy rate is now 90
(系统自动生成,下载前可以参看下载内容)

下载文件列表





DeepLearnToolbox-master

.......................\.travis.yml

.......................\CAE

.......................\...\caeapplygrads.m

.......................\...\caebbp.m

.......................\...\caebp.m

.......................\...\caedown.m

.......................\...\caeexamples.m

.......................\...\caenumgradcheck.m

.......................\...\caesdlm.m

.......................\...\caetrain.m

.......................\...\caeup.m

.......................\...\max3d.m

.......................\...\scaesetup.m

.......................\...\scaetrain.m

.......................\CNN

.......................\...\cnnapplygrads.m

.......................\...\cnnbp.m

.......................\...\cnnff.m

.......................\...\cnnnumgradcheck.m

.......................\...\cnnsetup.m

.......................\...\cnntest.m

.......................\...\cnntrain.m

.......................\...\test_example_CNN.m

.......................\CONTRIBUTING.md

.......................\create_readme.sh

.......................\data

.......................\....\mnist_uint8.mat

.......................\DBN

.......................\...\dbnsetup.m

.......................\...\dbntrain.m

.......................\...\dbnunfoldtonn.m

.......................\...\rbmdown.m

.......................\...\rbmtrain.m

.......................\...\rbmup.m

.......................\LICENSE

.......................\NN

.......................\..\nnapplygrads.m

.......................\..\nnbp.m

.......................\..\nnchecknumgrad.m

.......................\..\nneval.m

.......................\..\nnff.m

.......................\..\nnpredict.m

.......................\..\nnsetup.m

.......................\..\nntest.m

.......................\..\nntrain.m

.......................\..\nnupdatefigures.m

.......................\README.md

.......................\README_header.md

.......................\REFS.md

.......................\SAE

.......................\...\saesetup.m

.......................\...\saetrain.m

.......................\tests

.......................\.....\runalltests.m

.......................\.....\test_cnn_gradients_are_numerically_correct.m

.......................\.....\test_example_CNN.m

.......................\.....\test_example_DBN.m

.......................\.....\test_example_NN.m

.......................\.....\test_example_SAE.m

.......................\.....\test_nn_gradients_are_numerically_correct.m

.......................\util

.......................\....\allcomb.m

.......................\....\expand.m

.......................\....\flicker.m

.......................\....\flipall.m

.......................\....\fliplrf.m

.......................\....\flipudf.m

.......................\....\im2patches.m

.......................\....\isOctave.m

.......................\....\makeLMfilters.m

.......................\....\myOctaveVersion.m

.......................\....\normalize.m

.......................\....\patches2im.m

.......................\....\randcorr.m

.......................\....\randp.m

.......................\....\rnd.m

.......................\....\sigm.m

.......................\....\sigmrnd.m

.......................\....\softmax.m

.......................\....\tanh_opt.m

.......................\....\visualize.m

.......................\....\whiten.m

.......................\....\zscore.m

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