Exercise:Convolution and Pooling
From Ufldl
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== Convolution and Pooling == | == Convolution and Pooling == | ||
- | + | In this problem set, you will use the features you learned on 8x8 patches sampled from images from the STL10 dataset in [[Exercise:Exercise:Learning color features with Sparse Autoencoders | the earlier exercise on linear decoders]] for classifying 64x64 STL10 images by applying [[Feature extraction using convolution | convolution]] and [[Pooling | pooling]]. | |
In the file <tt>[http://ufldl.stanford.edu/wiki/resources/cnn_exercise.zip cnn_exercise.zip]</tt> we have provided some starter code. You should write your code at the places indicated "YOUR CODE HERE" in the files. | In the file <tt>[http://ufldl.stanford.edu/wiki/resources/cnn_exercise.zip cnn_exercise.zip]</tt> we have provided some starter code. You should write your code at the places indicated "YOUR CODE HERE" in the files. | ||
- | For this exercise, you will | + | For this exercise, you will need to modify'''<tt>cnnConvolve.m</tt>''' and '''<tt>cnnPool.m</tt>'''. |
=== Dependencies === | === Dependencies === | ||
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You will also need: | You will also need: | ||
- | * <tt> | + | * <tt>STL10Features.mat</tt> - saved features from [[Exercise:Learning_color_features_with_Sparse_Autoencoders]] |
* <tt>softmaxTrain.m</tt> (and related functions) from [[Exercise:Softmax Regression]] | * <tt>softmaxTrain.m</tt> (and related functions) from [[Exercise:Softmax Regression]] | ||
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=== Step 1: Learn color features === | === Step 1: Learn color features === | ||
- | + | In this step, we will load the color features you learned in [[Exercise:Learning_color_features_with_Sparse_Autoencoders]]. | |
- | [[File: | + | [[File:CNN_Features_Good.png|480px]] |