Miranda, M. S. :2023:
AI4LUC: pixel-based classification of land use and land cover via deep learning and a Cerrado image dataset
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4 referências similares encontradas (inclusive a original) buscando em 9 dentre 9 Arquivos. Data e hora local de busca: 27/07/2024 04:26. |
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Miranda:2023:PiClLa Miranda, M. S. :2023: AI4LUC: pixel-based classification of land use and land cover via deep learning and a Cerrado image dataset
metadados (BibTeX ❘ Refer ❘ Como citar? ❘ XML ❘ xrefer ❘ oai_dc ❘ mtd2-br ❘ Capa) <mtc-m21d.sid.inpe.br> |
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BendiniFRRSRMKLSH:2020:StCaBr Bendini, H. N., et al. :2020: Applying a Phenological Object-Based Image Analysis (PHENOBIA) for agricultural land classification: a study case in the brazilian cerrado
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BendiniFSKRSLH:2019:DeAgLa
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Bendini, H. N., et al. :2019: Detailed agricultural land classification in the Brazilian cerrado based on phenological information from dense satellite image time series
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Bendini:2019:AgLaCl Bendini, H. N. :2019: Agricultural land classification based on phenological information from dense time-series Landsat-like images in the brazilian Cerrado
metadados (BibTeX ❘ Refer ❘ Como citar? ❘ XML ❘ xrefer ❘ oai_dc ❘ mtd2-br ❘ Capa) <mtc-m21c.sid.inpe.br> |