What is a Fully Connected Layer?
A Fully Connected (FC) layer, aka a dense layer, is a type of layer used in artificial neural networks where each neuron or node from the previous layer is connected to each neuron of the current layer. It’s called “fully connected” because of this complete linkage. FC layers are typically found towards the end of neural network architecture and are responsible for producing final output predictions.
Fully Connected Layer vs Convolutional Layer
Confusion between Fully Connected Layers (FC) and Convolutional Layers is common due to terminology overlap. In CNNs, convolutional layers are used for feature extraction followed by FC layers for classification that makes it difficult for beginners to distinguish there roles.
This article compares Fully Connected Layers (FC) and Convolutional Layers (Conv) in neural networks, detailing their structures, functionalities, key features, and usage in deep learning architectures.
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