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Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging
Rice lodging severely affects harvest yield. Traditional evaluation methods and manual on-site measurement are found to be time-consuming, labor-intensive, and cost-intensive. In this study, a new method for rice lodging assessment based on a deep learning UNet (U-shaped Network) architecture was pr...
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| Veröffentlicht in: | Sensors (Basel) |
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| Hauptverfasser: | , , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6766838/ https://ncbi.nlm.nih.gov/pubmed/31500150 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19183859 |
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