Deep Learning Essentials

Fully connected or dense layer

One of the final layers in a CNN is often the fully connected layer, which is also known as a dense layer. Neurons in this layer are fully connected to all the activations in a previous layer. The output of this layer is usually the class score, where the number of neurons in this layer equals the number of classes typically.

Using the combination of the layers previously described, a CNN converts an input image to the final class scores. Each layer works in a different way and has different parameter requirements. The parameters in these layers are learned through a gradient descent-based algorithm in a back propagation way.