# Convolution with multiple input channel and multiple filters which have depth

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 3x3x3. 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.

• your guess is correct – shimao Jun 29 at 16:15