Meta Learning for Few-Shot One-Class Classification
We propose a method that can perform one-class classification given only a small number of examples from the target class and none from the others. We formulate the learning of meaningful features for one-class classification as a meta-learning problem in which the meta-training stage repeatedly sim...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-04-01
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| Series: | AI |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-2688/2/2/12 |