Reducing annotation effort in agricultural data: simple and fast unsupervised coreset selection with DINOv2 and K-means
The need for large amounts of annotated data is a major obstacle to adopting deep learning in agricultural applications, where annotation is typically time-consuming and requires expert knowledge. To address this issue, methods have been developed to select data for manual annotation that represents...
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| Principais autores: | , , , , , , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Frontiers Media S.A.
2025-05-01
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| Serija: | Frontiers in Plant Science |
| Teme: | |
| Online dostop: | https://www.frontiersin.org/articles/10.3389/fpls.2025.1546756/full |
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