Representing the architecture of a deep CNN Suppose I am feeding a $60\times60$ RGB image as the input to deep CNN with the first layer created using the following Keras code model.add(Conv2D(64, (3, 3), input_shape=(60, 60, 3))).

Will 64 filters be created for each channel (red, green and blue) of the image?
Is the following representation of the network correct? If 64 filters are created for each channel, then should I write &quot;3X64@58X58&quot;?
Will 64 filters be created for each channel (red, green and blue) of
the image?

No, Rather filters also will have 3 channels. It would be (333).
Its work something like this-

Borrowed from- http://datahacker.rs/convolution-rgb-image/
More here-
https://cs231n.github.io/convolutional-networks/.