RMSE for 3D regression of image data
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I am running a CNN on a reconstructed particle volume with intensity values of between 0 and 1. As I understand RMSE is the difference between the reconstructed and true values of intensity in the 3D volume. I am however getting values of RMSE more than 1. Surely this should not be the case if the maximum difference between the predicted and true value of any given voxel is 1. Can anyone explain why? What am I missing?
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Amanjit Dulai
2021년 7월 19일
How many values does your network output? If you are using regressionLayer in your network, it will not divide the loss by the number of outputs. So if you have 10 outputs, you will need to divide the loss by 10 to get the average loss per output element.
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Amanjit Dulai
2021년 8월 11일
So lets say the 3D volume that is being output is 5x5x5. That would give us 125 output values. The RMSE will not be normalized with respect to the number of output values. To normalize the RMSE with respect to this figure, you would divide it by the square root of 125. To normalise the MSE loss with respect to this figure, you would divide it by 125.
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