if you convolution a three-channel picture, the number of convolution kernels is 10. Since the final output of 10 feature map, does a convolution kernel have three channels? each convolution checks the image convolution of the three channels and then adds up to get a feature map?.
do I understand right?
your understanding is correct!
see the following figure:
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