Fully Connected layer

Presentation

This layer is the most common and simple layer, almost all neural network have once or more. The fully connected layer is a layer with simple neuron where all neurons is connected to all input.

Declaration

This is the function used to declare a fully connected layer.

template <class ... TOptimizer>
LayerModel FullyConnected(int numberOfNeurons, activation activation = activation::sigmoid, TOptimizer ... optimizers);

Arguments

• numberOfNeurons: The number of neurons in the layer.
• activation: The activation function of the neurons of the layer. See list of activation function

Here is an example of neural networks with 3 fully connected layer.

StraightforwardNeuralNetwork neuralNetwork({
        Input(28, 28, 1),
        FullyConnected(150, activation::ReLu),
        FullyConnected(70, activation::tanh),
        FullyConnected(10)
    });

See an example of GRU layer on dataset