neural network image classification (good, so-so, bad)
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Francesco Piantedosi am 9 Mär. 2016
Kommentiert: Francesco Piantedosi am 17 Mär. 2016
I would build a neural network to be feeded with images taken by my cell phone or camera. Starting from that image on some tools, ANN should identify 3 classes: OK, not so good, BAD.
Can someone address me on ho extract correct features from images and the feed my ANN? Any idea on how many layers and nodes per layers? I think I should have same neurons as input as pixel of my image, and 3 neurons as output.
Greg Heath am 11 Mär. 2016
The number of hidden nodes, H, should be the smallest number that will yield acceptable results. I typically use Ntrials = 10 or 20 nets for each value of H in an interval Hmin:dH:Hmax.
For most of the MATLAB examples
I have used numel(Hmin:dH:Hmax) = 10 which may have to be refined with another run with larger Hmin and smaller Hmax.
Hope this helps.
For examples search BOTH the NEWSGROUP and ANSWERS using
Explorer am 9 Mär. 2016
Neural Network images classification works fine. Accuracy of classification also depends on the features of the images. You haven't yet extracted features of images. Without features, you can not proceed.
First find an algorithm from research papers to extract features of images. And then you can ask for help in classification or feature matching using ANN.
By the way, Greg Heath has good knowledge of Neural Networks.
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