I am playing around with Mathematica's new Neural Network toolbox and am trying to teach a network to detect lines in quite noisy images.
An example Input image would look like the following:
The corresponding (desired) output is an image like this one (currently I am drawing those lines by hand...):
How would one approach this? In detail:
How many Input->Output pairs would I need? Currently I have about 100 but I guess this is not enough.
What Network architecture would you recommend? I tried a couple of combinations of Convolution and Ramp/Tanh layers but without amazing results.
Is there a more suited loss layer than the standard MeanSquare one for my purpose?
Would you even recommend using a neural network for this task?