Panicle Ratio Network : streamlining rice panicle measurement by deep learning with ultra-high-definition aerial images in the field
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Bibliographische Detailangaben
| Veröffentlicht in: | Journal of experimental botany. - 1985. - 73(2022), 19 vom: 02. Nov., Seite 6575-6588
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| 1. Verfasser: |
Guo, Ziyue
(VerfasserIn) |
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| Weitere Verfasser: |
Yang, Chenghai,
Yang, Wangnen,
Chen, Guoxing,
Jiang, Zhao,
Wang, Botao,
Zhang, Jian |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | Journal of experimental botany
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't
Deep convolutional neural network
effective tiller percentage
heading date
rice panicle ratio network
ultra-high-definition image
unmanned aerial vehicle |
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