Using neural network for classification
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Hi,
I have used GLCM in matlab to extract some texture features from an image. I did this using:
offsets0=[0 1; -1 1; -1;0, -1 1];
glcms=graycomatrix(img, 'Offset', Offsets0);
stats=graycoprops(glcms, 'all');
figure(2), plot([stats.correlation]) % i repeated this for the Contrast, Homogenity and Energy.
This produces the values:
Homgenity= 0.989 0.1468 0.1144 0.1342
Energy= 0.3366 0.3281 0.3340 0.3296
Contrast= 0.9542 0.9353 0.9474 0.9384
Correlation= 0.9798 0.9699 0.9766 0.9707
I want to use the nnprtool GUI to classify these features however I am unsure how to prepare thesr features for input into the neural network.
Can anyone help me ??
Thanks :)
1 Kommentar
Greg Heath
am 11 Apr. 2014
Insufficient information.
What are the classes?
How many input features per example?
How many input/output examples?
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