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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Bibliographic Details
Main Authors: Laura Gómez-Zamanillo, Nagore Portilla, Artzai Picón, Itziar Egusquiza, Ramón Navarra-Mestre, Andoni Elola, Arantza Bereciartua-Perez
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Plant Science
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Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2025.1546756/full
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