Please use this identifier to cite or link to this item:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1121648
Title: | A machine learning framework to predict nutrient content in valencia-orange leaf hyperspectral measurements. |
Authors: | OSCO, L. P.![]() ![]() RAMOS, A. P. M. ![]() ![]() PINHEIRO, M. M. F. ![]() ![]() MORIYA, E. A. S. ![]() ![]() IMAI, N. N. ![]() ![]() ESTRABIS, N. ![]() ![]() IANCZYK, F. ![]() ![]() ARAÚJO, F. F. ![]() ![]() LIESENBERG, V. ![]() ![]() JORGE, L. A. de C. ![]() ![]() LI, J. ![]() ![]() MA, L. ![]() ![]() GONÇALVES, W. N. ![]() ![]() MARCATO JUNIOR, J. ![]() ![]() CRESTE, J. E. ![]() ![]() |
Affiliation: | LUCIO ANDRE DE CASTRO JORGE, CNPDIA. |
Date Issued: | 2020 |
Citation: | Remote Sensing, n. 12, v. 6, a. 906, 2020. |
Pages: | 1 - 21 |
Keywords: | Proximal sensor Macronutrient Micronutrient |
Language: | Ingles |
DOI: | 10.3390/rs12060906 |
Type of Material: | Artigo de periódico |
Access: | openAccess |
Appears in Collections: | Artigo em periódico indexado (CNPDIA)![]() ![]() |
Files in This Item:
File | Description | Size | Format | |
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P-A-Machine-Learning-Framework-to-Predict-Nutrient-....pdf | 4,7 MB | Adobe PDF | ![]() View/Open |