Remotely sensed imagery and machine learning for mapping of sesame crop in the Brazilian Midwest

Author:

de Azevedo Raul Pio,Dallacort Rivanildo,Boechat Cácio LuizORCID,Teodoro Paulo Eduardo,Teodoro Larissa Pereira Ribeiro,Rossi Fernando Saragosa,Filho Washington Luiz Félix Correia,Della-Silva João Lucas,Baio Fabio Henrique Rojo,Lima Mendelson,Silva Junior Carlos Antonio daORCID

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference46 articles.

1. Köoppen ’ s climate classification map for Brazil;Alvares;Meteorol. Z.,2013

2. A review on the utilization of sesame as functional food;Asghar;American Journal of Food and Nutrition,2014

3. Machine learning in remote sensing data processing;Camps-Valls,2009

4. Weed detection in sesame fields using a YOLO model with an enhanced attention mechanism and feature fusion;Chen;Comput. Electron. Agric.,2022

5. Acompanhamento da Safra Brasileira - SAFRA 2019/20 (Março 2020);Conab;Companhia Nacional de Abastecimento,2020

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