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Endel

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University of Tartu

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Image processing, pattern recognition, neural networks

 

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Comments and Ratings by Endel
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27 Jan 2014 CNN - Convolutional neural network class This project provides matlab class for implementation of convolutional neural networks. Author: Mihail Sirotenko

I have a problem with understanding the actual architecture of this network. Usually, LeCun et al have used different weights for the connections from different feature maps of a previous layer (something that looks like 3D kernel). Therefore, the number of weights of a convolution layer (assuming full map of connections) is kernelHeight*kernelWidth*numFeatMapsLayer(k)*numFeatMapsLayer(k-1). I am not sure, but it seems that there are kernelHeight*kernelWidth*numFeatMapsLayer(k) different weights used in this program. Does it means that the connections from different feature maps of a previous layer to a particular feature map of the next layer have the same weights? Or maybe, I misunderstand something?

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