why a Gray image is shown as a Colored image on CNN deep learning ?
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CNN network of deep learning reads my gray image as a colored image. Whenever, tried to change the diminsions to gray [ 227 227 1], the system gives me error
layers = [
imageInputLayer([227 227 3],"Name","data")
convolution2dLayer([11 11],94,"Name","conv1","BiasLearnRateFactor",2,"Stride",[4 4])
reluLayer("Name","relu1")
crossChannelNormalizationLayer(5,"Name","norm1","K",1)
maxPooling2dLayer([3 3],"Name","pool1","Stride",[2 2])
groupedConvolution2dLayer([5 5],94,2,"Name","conv2","BiasLearnRateFactor",2,"Padding",[2 2 2 2])
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Image Analyst
am 14 Dez. 2020
That's right. For most predefined network architectures, they were built to handle color images. Just make your gray scale images into color images and don't worry about it. The network will eventually learn during training that it doesn't need to use the other two color channels.
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Image Analyst
am 15 Dez. 2020
WHAT did not work? The cat() function? Or your training/classification/prediction process?
I can't really download all your training images. Sorry. I suggest you call tech support and ask them to walk you through it step by step.
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