Barely-Supervised Learning: Semi-supervised Learning with Very Few Labeled Images
Barely-Supervised Learning: Semi-supervised Learning with Very Few Labeled Images
This paper tackles the problem of semi-supervised learning when the set of labeled samples is limited to a small number of images per class, typically less than 10, problem that we refer to as barely-supervised learning. We analyze in depth the behavior of a state-of-the-art semi-supervised method, FixMatch, which relies …