Fig. 4.

The structure of an CNN, usually consisting of three distinct layers: the convolution layer, the pooling layer, and a final fully-connected layer (Fig. 2(b)), where the convolution layer and pooling (subsampling) layer may be connected several times before a final fully-connected layer is encountered. An image mapped by a convolution layer is called a feature map, which triggers attention of many computer scientists. Figure created by Aphex34 distributed under a CC BY-SA 4.0 license (from Wikimedia Commons).