Convolution layers are often followed by a pooling layer.

Name: Convolution layers are often followed by a pooling layer.
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Pooling layers are typically used after convolutional layers in a neural network architecture to reduce the spatial dimensions of the input volume for the next layer, which helps in reducing the number of parameters and computation in the network, and also helps in achieving translation invariance.

Convolution Layers Are Often Followed by a Pooling Layer