Fig. 3.

Schematic of a fully connected neural network. $\mathit{left}:$ An artificial neuron or perceptron, where the output y is calculated as a sum of weighted inputs $x=[x_1,x_2,...,x_n]$ (with weights $w=[w_1,w_2,...,w_n]$) and a bias b, optionally passed through an activation function f. $\mathit{right}:$ The fully connected neural network is created by connecting these neurons into many layers, where the outputs of one layer serve as the inputs to the following layer. The network depicted here consists of N inputs and M outputs