Is there such a thing as this? This is my aim (the field is image pattern recognition):-
myInput -> Neural Network A -> Likelihood of being objectA
myInput -> Neural Network B -> Likelihood of being objectB
myInput -> Neural Network C -> Likelihood of being objectC
myInput -> Neural Network D -> Likelihood of being objectD
I want to train several neural networks to recognise a different particular object, run my input through each and get returned a number between 0 and 1 that says how likely the input is the object the network is trained for.
Could someone suggest a network for this? I had a look in samples/editor/som/SOMImageNet.ser and this uses a WinnerTakesAll layer. Which obviously doesn't give me a likelihood.
Could someone suggest an alternate approach or a way to do this?
I've just seen this thread:-
and realised that this is what I want.
Where can I get the calculated euclidean distance of the kohonensynapse from?
Thanks for any help,
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