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DeepLearnToolbox

于 2014-05-19 发布 文件大小:14405KB
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代码说明:

  深度学习工具包,内有各大牛提出深度学习方法的matlab实现,挺全的(Deep learning toolkit, there are major cattle raised deep learning method matlab realize, quite wide)

文件列表:

DeepLearnToolbox
................\.travis.yml,249,2013-12-16
................\CAE
................\...\caeapplygrads.m,1219,2013-12-16
................\...\caebbp.m,917,2013-12-16
................\...\caebp.m,1011,2013-12-16
................\...\caedown.m,259,2013-12-16
................\...\caeexamples.m,754,2013-12-16
................\...\caenumgradcheck.m,3618,2013-12-16
................\...\caesdlm.m,845,2013-12-16
................\...\caetrain.m,1148,2013-12-16
................\...\caeup.m,489,2013-12-16
................\...\max3d.m,173,2013-12-16
................\...\scaesetup.m,1937,2013-12-16
................\...\scaetrain.m,270,2013-12-16
................\CNN
................\...\cnnapplygrads.m,575,2013-12-16
................\...\cnnbp.m,2141,2013-12-16
................\...\cnnff.m,1774,2013-12-16
................\...\cnnnumgradcheck.m,3430,2013-12-16
................\...\cnnsetup.m,2019,2013-12-16
................\...\cnntest.m,193,2013-12-16
................\...\cnntrain.m,845,2013-12-16
................\CONTRIBUTING.md,544,2013-12-16
................\create_readme.sh,744,2013-12-16
................\data
................\....\mnist_uint8.mat,14735220,2013-12-16
................\DBN
................\...\dbnsetup.m,557,2013-12-16
................\...\dbntrain.m,232,2013-12-16
................\...\dbnunfoldtonn.m,425,2013-12-16
................\...\rbmdown.m,90,2013-12-16
................\...\rbmtrain.m,1401,2013-12-16
................\...\rbmup.m,89,2013-12-16
................\htm" target=_blank>LICENSE,1313,2013-12-16
................\NN
................\..\nnapplygrads.m,628,2013-12-16
................\..\nnbp.m,1638,2013-12-16
................\..\nnchecknumgrad.m,704,2013-12-16
................\..\nneval.m,772,2013-12-16
................\..\nnff.m,1849,2013-12-16
................\..\nnpredict.m,188,2013-12-16
................\..\nnsetup.m,1844,2013-12-16
................\..\nntest.m,180,2013-12-16
................\..\nntrain.m,2414,2013-12-16
................\..\nnupdatefigures.m,1858,2013-12-16
................\README.md,8730,2013-12-16
................\README_header.md,2256,2013-12-16
................\REFS.md,950,2013-12-16
................\SAE
................\...\saesetup.m,132,2013-12-16
................\...\saetrain.m,308,2013-12-16
................\tests
................\.....\runalltests.m,165,2013-12-16
................\.....\test_cnn_gradients_are_numerically_correct.m,552,2013-12-16
................\.....\test_example_CNN.m,981,2013-12-16
................\.....\test_example_DBN.m,1031,2013-12-16
................\.....\test_example_NN.m,3247,2013-12-16
................\.....\test_example_SAE.m,934,2013-12-16
................\.....\test_nn_gradients_are_numerically_correct.m,749,2013-12-16
................\util
................\....\allcomb.m,2618,2013-12-16
................\....\expand.m,1958,2013-12-16
................\....\flicker.m,208,2013-12-16
................\....\flipall.m,80,2013-12-16
................\....\fliplrf.m,543,2013-12-16
................\....\flipudf.m,576,2013-12-16
................\....\im2patches.m,313,2013-12-16
................\....\isOctave.m,108,2013-12-16
................\....\makeLMfilters.m,1895,2013-12-16
................\....\normalize.m,97,2013-12-16
................\....\patches2im.m,242,2013-12-16
................\....\randcorr.m,283,2013-12-16
................\....\randp.m,2083,2013-12-16
................\....\rnd.m,49,2013-12-16
................\....\sigm.m,48,2013-12-16
................\....\sigmrnd.m,126,2013-12-16
................\....\softmax.m,256,2013-12-16
................\....\tanh_opt.m,54,2013-12-16
................\....\visualize.m,1072,2013-12-16
................\....\whiten.m,183,2013-12-16
................\....\zscore.m,137,2013-12-16

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    已有的文本过滤受限,所以对现有的文本过滤软件进行了算法改进,对现有的问题进行分析,故而有着实用价值,但是文本过滤仍然有着不能弥补对图形图象的无效,所以有必要对图象视频等进行过滤(Already limited text filtering, so the existing text filtering software algorithms to improve on the existing analysis of the problem the club would have practical value, but still have a text filter should not make up for the graphic image is invalid, there is necessary to filter the video image)
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