Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging (2020)
- Authors:
- USP affiliated authors: SILVA, CLÍSSIA BARBOZA DA - ESALQ ; ROSAS, JORGE TADEU FIM - ESALQ
- Unidade: ESALQ
- DOI: 10.3390/s20154319
- Subjects: APRENDIZADO COMPUTACIONAL; BRACHIARIA; ESPECTROSCOPIA INFRAVERMELHA; RAIOS X; SEMENTES; TRANSFORMADA DE FOURIER
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este artigo possui versão em acesso aberto
- URL de acesso aberto
- PDF de acesso aberto
- Versão do Documento: Versão publicada (Published version)
-
Status: Artigo publicado em periódico de acesso aberto (Gold Open Access) -
ABNT
MEDEIROS, André Dantas de et al. Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging. Sensors, v. 20, n. 15, p. 1-13, 2020Tradução . . Disponível em: https://doi.org/10.3390/s20154319. Acesso em: 14 mar. 2026. -
APA
Medeiros, A. D. de, Silva, L. J. da, Ribeiro, J. P. O., Ferreira, K. C., Rosas, J. T. F., Santos, A. A., & Silva, C. B. da. (2020). Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging. Sensors, 20( 15), 1-13. doi:10.3390/s20154319 -
NLM
Medeiros AD de, Silva LJ da, Ribeiro JPO, Ferreira KC, Rosas JTF, Santos AA, Silva CB da. Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging [Internet]. Sensors. 2020 ; 20( 15): 1-13.[citado 2026 mar. 14 ] Available from: https://doi.org/10.3390/s20154319 -
Vancouver
Medeiros AD de, Silva LJ da, Ribeiro JPO, Ferreira KC, Rosas JTF, Santos AA, Silva CB da. Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging [Internet]. Sensors. 2020 ; 20( 15): 1-13.[citado 2026 mar. 14 ] Available from: https://doi.org/10.3390/s20154319 - Condicionamento fisiológico de sementes de pimentão com biorreguladores
- Interactive machine learning for soybean seed and seedling quality classification
- Spatial variability of soil apparent electrical conductivity- effect of the number of subsamples
- Influence of tillage systems on soil physical properties, spectral response and yield of the bean crop
- A Novel Vegetation Index for Coffee Ripeness Monitoring Using Aerial Imagery
- Soil chemical alteration due to treated swine wastewater application in a semi-arid area in Southeastern Brazil
- Quality assessment of coffee beans through computer vision and machine learning algorithms
- Low-cost system for radiometric calibration of UAV-based multispectral imagery
- Coffee ripeness monitoring using a UAV-mounted low-cost multispectral camera
- Spatial and temporal behavior of coffee rust in C. canephora and its effects on crop yield
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 3002377-Machine Learning ... | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
