Improving the identification of haploid maize seeds using convolutional neural networks (2021)
- Authors:
- USP affiliated authors: FRITSCHE NETO, ROBERTO - ESALQ ; CAMPOS, GABRIELA ROMERO - ESALQ ; SABADIN, JOSÉ FELIPE GONZAGA - ESALQ ; GALLI, GIOVANNI - ESALQ ; GEVARTOSKY, RAYSA - ESALQ
- Unidade: ESALQ
- DOI: 10.1002/csc2.20487
- Subjects: MILHO; SEMENTES; REDES NEURAIS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Crop Science
- ISSN: 0011-183X
- Volume/Número/Paginação/Ano: p. 1-11, 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SABADIN, Felipe et al. Improving the identification of haploid maize seeds using convolutional neural networks. Crop Science, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1002/csc2.20487. Acesso em: 26 dez. 2025. -
APA
Sabadin, F., Galli, G., Borsato, R., Gevartosky, R., Campos, G. R., & Fritsche-Neto, R. (2021). Improving the identification of haploid maize seeds using convolutional neural networks. Crop Science, 1-11. doi:10.1002/csc2.20487 -
NLM
Sabadin F, Galli G, Borsato R, Gevartosky R, Campos GR, Fritsche-Neto R. Improving the identification of haploid maize seeds using convolutional neural networks [Internet]. Crop Science. 2021 ; 1-11.[citado 2025 dez. 26 ] Available from: https://doi.org/10.1002/csc2.20487 -
Vancouver
Sabadin F, Galli G, Borsato R, Gevartosky R, Campos GR, Fritsche-Neto R. Improving the identification of haploid maize seeds using convolutional neural networks [Internet]. Crop Science. 2021 ; 1-11.[citado 2025 dez. 26 ] Available from: https://doi.org/10.1002/csc2.20487 - A novel way to validate UAS-based high-throughput phenotyping protocols using in silico experiments for plant breeding purposes
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Informações sobre o DOI: 10.1002/csc2.20487 (Fonte: oaDOI API)
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