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Document type:
Zeitschriftenaufsatz 
Author(s):
Ayyad, A.; Navab, N.; Elhoseiny, M.; Albarqouni, S. 
Title:
Semi-Supervised Few-Shot Learning with Local and Global Consistency 
Abstract:
Learning from a few examples is a key characteristic of human intelligence that AI researchers have been excited about modeling. With the web-scale data being mostly unlabeled, few recent works showed that few-shot learning performance can be significantly improved with access to unlabeled data, known as semi-supervised few shot learning (SS-FSL). We introduce a SS-FSL approach that we denote as Consistent Prototypical Networks (CPN), which builds on top of Prototypical Networks. We propose new...    »
 
Keywords:
ICML,CAMP 
Journal title:
arXiv preprint arXiv:1903.02164 
Year:
2019