# ReLu layer in CNN (RGB Image)

I am able to get convoluted values from RGB Image lets say for each channel. So I have red channel with values: -100,8,96,1056,-632,2,3....

Now what I do is that I normalize this values in range 0-255 because that is range of rgb values basically with code Math.Max(minValue, Math.Min(maxValue, currentValue)).

But I don't understand how relu works in CNN. From my point of view I am alredy doing it in my normalization right? Because ReLu layer is from 0 to x where max value of x is 255.

So my question is where should be applied ReLu in RGB image after convolution? (After convolution and normalization values are alredy in range 0-255)

• You should not normalize after the convolution. The point of ReLU is to introduce a non-linearity in the computation, not to force the values into a specific range.
– noe
Mar 10 at 18:54
• @noe but thats tricky becuase rgb is fixed to range 0-255 so when I use higher number then 255 I get error. Mar 10 at 18:57
• The output of a convolution is not to be interpreted directly as an RGB image, and the output value range does not need to be in [0, 255]. Why do you think it should be?
– noe
Mar 10 at 19:02