Data format in neural network

2013 10 17
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更新时间：2013 10 29
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Hi all, Kindly i really appreciate your help , i have a plan to make skin color segmentation by using neural network , i just have a problem how to format my database ,input vectors it's gona be YCbCr color space and the target 1,0 skin,non skin
Thanks

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Greg Heath
Greg Heath 2013-10-18
编辑：Greg Heath 2013-10-23

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N pairs of I-dimensional inputs and 1-dimensional targets.
[ I N ] = size(inputs)
[ O N ] = size(targets) % O =1
net = patternnet; % First consider defaults
help patternnet
If you have an older version of the NNTBX, try newpr.
help newpr
You may want to practice on the classification/pattern-recognition data in
help nndatasets.
Thank you for formally accepting my answer
Greg

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Yasir
Yasir 2013-10-18

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Hi Greg, i really appreciate your kind reply but still now not so clear let's suppose that RGB (119,79,53) these pixels represent skin color while (200,34,23) nonskin are am going to format it as below
[119 79 53;200 34 23] %input vectors [1 1 1 ;0 0 0]%output vector ------ 1- skin , 0-nonskin
and then i fed up these to NN to train it , i really appreciate your clarification because the examples in MATLAB for wine classification the DB not so clear just [X,T]=wine_dataset; % X input ,T target
Thanks for your cooperation

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Greg Heath
Greg Heath 2013-10-19
PLEASE USE THE COMMENT BOX, NOT THE ANSWER BOX FOR FOLLOW UP QUESTIONS AND COMMENTS.
NOT ONLY IS IT CONFUSING, IT MESSES UP MATLABS QUESTION/ANSWER/COMMENT BEAN COUNTING.
THANKS.
GREG
Greg Heath
Greg Heath 2013-10-19
I don't understand your confusion. If an I dimensional input column vector corresponds to an O dimensional target output column vector, the dimensions of the input and output target matrices are
[ I N ] = size(input)
[ O N ] = size(target)
[ X, T ] = wine_dataset;
[ I N ] = size(X)
[ O N ] = size(T)
whos X T
I = 13
N = 178
O = 3
N = 178
Name Size Bytes Class Attributes
T 3x178 4272 double
X 13x178 18512 double
Hope this helps.
Greg
Yasir
Yasir 2013-10-19
apology okay i will try to overcome it Thanks a lot Greg
Image Analyst
Image Analyst 2013-10-29
I marked Greg's answer as accepted for you because you forgot to.

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