Extending Contrastive Learning to Unsupervised Redundancy Identification
Modern deep neural network (DNN)-based approaches have delivered great performance for computer vision tasks; however, they require a massive annotation cost due to their data-hungry nature. Hence, given a fixed budget and unlabeled examples, improving the quality of examples to be annotated is a cl...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2022-02-01
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| Серии: | Applied Sciences |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2076-3417/12/4/2201 |
| Метки: |
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