中文说明：先利用卷及神经网络提取数据特征，再加svm进行分类
English Description：
Firstly, the volume and neural network are used to extract data features, and then SVM is used to classify
Firstly, the volume and neural network are used to extract data features
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中文说明：先利用卷及神经网络提取数据特征，再加svm进行分类
English Description：
Firstly, the volume and neural network are used to extract data features, and then SVM is used to classifyCNNSVM-master
.............\.gitattributes
.............\.gitignore
.............\CNNSVM
.............\......\cnn
.............\......\...\cnnapplygrads.m
.............\......\...\cnnbp.m
.............\......\...\cnnff.m
.............\......\...\cnnnumgradcheck.m
.............\......\...\cnnsetup.m
.............\......\...\cnntest.m
.............\......\...\cnntrain.m
.............\......\...\test_example_CNN.m
.............\......\cnn-model
.............\......\.........\epoch10.mat
.............\......\.........\readme.txt
.............\......\CNN.m
.............\......\CNNSVM.m
.............\......\cnn_predict.m
.............\......\data
.............\......\....\mnist_uint8.mat
.............\......\epoch_by_epoch.m
.............\......\feat-code
.............\......\.........\compute_features.m
.............\......\.........\compute_feature_dim.m
.............\......\.........\compute_gradient.m
.............\......\.........\compute_gradient_features.m
.............\......\.........\compute_gradient_features.m~
.............\......\.........\compute_sphog_features.m
.............\......\.........\concat_features.m
.............\......\.........\cumsum2D.m
.............\......\.........\get_sampling_grid.m
.............\......\.........\normalize_response.m
.............\......\generate_cnn_feature.m
.............\......\Readme.md
.............\......\svm
.............\......\...\display_images.m
.............\......\...\libsvmread.c
.............\......\...\libsvmread.mexw64
.............\......\...\libsvmwrite.c
.............\......\...\libsvmwrite.mexw64
.............\......\...\make.m
.............\......\...\Makefile
.............\......\...\normalize_data.m
.............\......\...\htm" target=_blank>README
.............\......\...\read_data.m
.............\......\...\svmpredict.c
.............\......\...\svmpredict.mexw64
.............\......\...\svmtrain.c
.............\......\...\svmtrain.mexw64
.............\......\...\svm_model_matlab.c
.............\......\...\svm_model_matlab.h
.............\......\svmmnistfea.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