Fully Self-Supervised Out-of-Domain Few-Shot Learning with Masked Autoencoders
Few-shot learning aims to identify unseen classes with limited labelled data. Recent few-shot learning techniques have shown success in generalizing to unseen classes; however, the performance of these techniques has also been shown to degrade when tested on an out-of-domain setting. Previous work,...
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| Autori principali: | , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2024-01-01
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| Serie: | Journal of Imaging |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2313-433X/10/1/23 |
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