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cnnPool.m
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cnnPool.m
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function pooledFeatures = cnnPool(poolDim, slide, convolvedFeatures)
%cnnPool Pools the given convolved features
%
% Parameters:
% poolDim - dimension of pooling region
% convolvedFeatures - convolved features to pool (as given by cnnConvolve)
% convolvedFeatures(imageRow, imageCol, featureNum, imageNum)
%
% Returns:
% pooledFeatures - matrix of pooled features in the form
% pooledFeatures(poolRow, poolCol, featureNum, imageNum)
%
numImages = size(convolvedFeatures, 4);
numFilters = size(convolvedFeatures, 3);
convolvedDimH = size(convolvedFeatures, 2);
convolvedDimV = size(convolvedFeatures, 1);
pooledFeatures = zeros((convolvedDimV-poolDim)/slide + 1, ...
(convolvedDimH - poolDim) / slide + 1, numFilters, numImages);
% Instructions:
% Now pool the convolved features in regions of poolDim x poolDim,
% to obtain the
% (convolvedDim/poolDim) x (convolvedDim/poolDim) x numFeatures x numImages
% matrix pooledFeatures, such that
% pooledFeatures(poolRow, poolCol, featureNum, imageNum) is the
% value of the featureNum feature for the imageNum image pooled over the
% corresponding (poolRow, poolCol) pooling region.
for imageNum = 1:numImages
for filterNum = 1:numFilters
aux = conv2(convolvedFeatures(:, :, filterNum, imageNum), ones(poolDim), 'valid');
pooledFeatures(:, :, filterNum, imageNum) = aux(1:slide:end, 1:slide:end) ./ (poolDim .^ 2);
end
end
end