Few-shot object detection based on positive-sample improvement
Traditional object detectors based on deep learning rely on plenty of labeled samples, which are expensive to obtain. Few-shot object detection (FSOD) attempts to solve this problem, learning detection objects from a few labeled samples, but the performance is often unsatisfactory due to the scarcit...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
KeAi Communications Co., Ltd.
2023-10-01
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| Series: | Defence Technology |
| Assuntos: | |
| Acceso en liña: | http://www.sciencedirect.com/science/article/pii/S2214914722001660 |
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