33 citations · 33 across the 1 of their papers we have counts for
2 papers
cs.CV2021
Fine-Grained Adversarial Semi-supervised Learning
Daniele Mugnai, Federico Pernici, Francesco Turchini +1
In this paper we exploit Semi-Supervised Learning (SSL) to increase the amount of training data to improve the performance of Fine-Grained Visual Categorization (FGVC). This proble…
cs.LG2020★ 33 cited
Class-incremental Learning with Pre-allocated Fixed Classifiers
Federico Pernici, Matteo Bruni, Claudio Baecchi +2
In class-incremental learning, a learning agent faces a stream of data with the goal of learning new classes while not forgetting previous ones. Neural networks are known to suffer…