my project is about facial expression recognition.
for the classification of the emotions i want to train a neural network having an input 20 points taken from the whole face by the vision.CornerDetector function. so each point feature is represented by its X and its Y.
my database contain 110 smiling photos and 95 neutral ones. so that, the whole matrix of smiling faces, for example, has a size of 20x220.
any ideas about how to train my neural network using these features?

1 commentaire

Saud Alramzi
Saud Alramzi le 20 Avr 2016
Hello,
I am working on the same project, did it work for you by chance?
Thanks, Saud

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 Réponse acceptée

Greg Heath
Greg Heath le 31 Mai 2013

0 votes

Use patternnet
Ns = 110, Nn = 95, N=Ns+Nn = 205 (NOT 220), I = 20, O = 2
[ I N ] = size(input)
[ O N ] = size(target)
with
target = [ targets targetn ]
targets = repmat([1;0],1,Ns)
targetn = repmat([0;1],1,Nn)
Hope this helps.
Thank you for formally accepting my answer
Greg

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