How does the convolution work for an input which has multiple channels convolving with filters that also have depth.
For example, assume somewhere in the network we have a
5x5x3being an input to a convolution layer.
The layer has 2 filters which have size
3x3, the depth of the filters would therefore be
3 because of the input, so each filter is actually
Now how does the convolution work in this case.
My guess is that a convolution happens with each specific channel. E.g. Filter 1 channel 1 convolved with input channel 1, Filter 1 channel 2 convolved with input channel 2, and Filter 1 channel 3 convolved with input channel 3. Is this what happens?
Sorry if this seems like a basic question. I have read tutorials but they mostly show convolution with 1 channel only. If you could link any tutorials which explains this it would quite helpful.