Hi,
Please provide help regarding how the transposedConv2dLayer works.
I am struggling to understand the following helper function
function out = createUpsampleTransponseConvLayer(factor,numFilters)filterSize = 2*factor - mod(factor,2); cropping = (factor-mod(factor,2))/2;numChannels = 1;out = transposedConv2dLayer(filterSize,numFilters, ... 'NumChannels',numChannels,'Stride',factor,'Cropping',cropping);end
from the example: https://uk.mathworks.com/help/deeplearning/examples/image-to-image-regression-using-deep-learning.html
How does the filtersize and stride affect the output of this layer?
What's the difference between this layer and a simple upsampling layer?
whether the weights are somehow transposed or learned from scratch?
Best Answer