What Are Recurrent Neural Networks And How Do They Work?
When a convolution layer follows the preliminary layer, the construction of the CNN can become hierarchical, as later layers can see pixels within the receptive fields of earlier layers. After each operation, a CNN applies a rectified linear unit transformation to the characteristic map, introducing nonlinearity into the model. Hinton, “A scalable hierarchical distributed language model,” in Proc. Use AI…