CNN: Which channel gives the most informations?
IF a color channel is the most important, you can check manually by getting the weights of the input convolution layer. They will be in (filtersizex x filtersizey x 3) X the number of filters. you then need to add the weights so you get (1 x 3) X the number of filters. So you have for each filter the most important channel, if you need this for the whole network add them all together and you end with an (1 x 3) array, the max of this is the most important channel.
while working with CNNs I was wondering which of my Input Channels gives the most information to the neural network for the prediction.
For example: The is a image of a frog. The CNN is suppose to predict which kind of animal is in the image.
So because frogs are green most of the time, the CNN uses the channel G from RGB the most for prediction.
Is there a way of finding out which channel is the most important for a specific neural network?