Transfer learning

Transfer learning corresponds to a redirection of trained models for one use to another use.

Neural networks are made of 2 blocks

• the one building the features
• the one using the features for classification/regression purposes

Starting from such a neural network, one of the possibilities offered to the user to transfer the knowledge acquired during the training for a given problem to another problem consists in keeping the layers generating the features and re-training the layers doing the classification.