Building One-Shot Semi-Supervised (BOSS) Learning Up to Fully Supervised Performance

Reaching the performance of fully supervised learning with unlabeled data and only labeling one sample per class might be ideal for deep learning applications. We demonstrate for the first time the potential for building one-shot semi-supervised (BOSS) learning on CIFAR-10 and SVHN up to attain test...

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Detalles Bibliográficos
Autores principales: Smith, Leslie N., Conovaloff, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200967/
https://www.ncbi.nlm.nih.gov/pubmed/35719691
http://dx.doi.org/10.3389/frai.2022.880729

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9200967/
https://www.ncbi.nlm.nih.gov/pubmed/35719691
http://dx.doi.org/10.3389/frai.2022.880729

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