Specifically, meta-learning is executed over a pretrained network for few-shot classification. Furthermore, self-supervised learning is exploited to fit the target domain distribution by training on ...

Semi-supervised learning is a machine learning approach that tackles the challenge of having a large set of unlabeled data and few labeled ones. In this paper we adopt a semi-supervised self-training ...