Fully Connected Layers

Fully connected layers are components of neural networks where each input is connected to every neuron in the layer. Think of it as a network of pathways where all information from the previous layer influences each new calculation. These layers analyze features extracted earlier and combine them to recognize patterns or make decisions. They are essential for integrating information to produce the final output, such as classifying an image or understanding language. Essentially, fully connected layers act as the decision-making hub, synthesizing all processed data into a meaningful result.