Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes

Raphael Lafargue, Yassir Bendou, Bastien Pasdeloup +4

When training data is scarce, it is common to make use of a feature extractor that has been pre-trained on a large base dataset, either by fine-tuning its parameters on the ``targe…