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Automated Counting of Rice Panicle by Applying Deep Learning Model to Images from Unmanned Aerial Vehicle Platform
The number of panicles per unit area is a common indicator of rice yield and is of great significance to yield estimation, breeding, and phenotype analysis. Traditional counting methods have various drawbacks, such as long delay times and high subjectivity, and they are easily perturbed by noise. To...
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| Pubblicato in: | Sensors (Basel) |
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| Autori principali: | , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6679257/ https://ncbi.nlm.nih.gov/pubmed/31337086 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19143106 |
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