# Tag Info

The first formula you quote is for an image with one input channel and one output channel, it just focuses on height and width. In this case, if we consider a 5x5 convolution, the Kernel will just have size 5x5, $m$ and $n$ and going from -2 to +2. Now if our input has 3 channels (RGB, but could be feature maps). we need to use each channel as an input, and ...