Input layer Deep Learning
noun phrase
Definition: The first layer of a neural network that receives or contains the input feature vector and forwards it to subsequent hidden or output layers for processing. [Google ML Glossary].
Example in context: “The structure of a feed-forward (where input only flows in one direction within the network) Artificial Neural Network (ANN) consists of an input layer, intermediate hidden layers, and an output layer.” [Gambín et al. 2024]
Related terms: input nodes, feature layer (usage-dependent), hidden layer (next-stage contrast)