A simple convolutional neural network with linear neurons. Structure: input->convolution->max pooling->convolution->max pooling->fully connected. Compile the max pooling function in C++ first by typing mex MaxPooling.cpp . The data can be downloaded in http://ai.stanford.edu/~amaas/data/data.zip The data loading functions can be downloaded in http://ufldl.stanford.edu/wiki/index.php/Using_the_MNIST_Dataset About 98 classification accuracy for 50 epochs of all training data.

cnn_linear_max-master
.....................\cnnTest.m
.....................\cnnTrain.m
.....................\Debug
.....................\.....\MaxPooling.pch
.....................\.....\vc60.idb
.....................\.....\vc60.pdb
.....................\MaxPooling.cpp
.....................\MaxPooling.dsp
.....................\MaxPooling.dsw
.....................\MaxPooling.ncb
.....................\MaxPooling.opt
.....................\MaxPooling.plg
.....................\README.md
.....................\upsampleMax.m

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