Sugarcane Harvesting Quality by Digital Image Processing-Reference-Cited by-同舟云学术

Sugarcane Harvesting Quality by Digital Image Processing

Published:2020-08-08 Issue:1 Volume:23 Page:209-218
ISSN:0972-1525
Container-title:Sugar Tech
language:en
Short-container-title:Sugar Tech

Author:

De Moura Araújo Guilherme^ORCID,dos Santos Fernando Ferreira Lima,de Almeida Samira Luns Hatum,Martins Rodrigo Nogueira,Voltarelli Murilo Aparecido,Paixão Carla Segatto Strini,de Assis de Carvalho Pinto Francisco

Publisher

Springer Science and Business Media LLC

Subject

Agronomy and Crop Science

Link

http://link.springer.com/content/pdf/10.1007/s12355-020-00867-2.pdf

Reference31 articles.

1. Alencastre-Miranda, Moises, Joseph R. Davidson, Richard M. Johnson, Herman Waguespack, and Hermano Igo Krebs. 2018. Robotics for sugarcane cultivation: Analysis of billet quality using computer vision. IEEE Robotics and Automation Letters 3 (4): 3828–3835. https://doi.org/10.1109/lra.2018.2856999.

2. Aquino, Arturo, Ignacio Barrio, Maria-Paz Diago, Borja Millan, and Javier Tardaguila. 2018. vitisBerry: An Android-smartphone application to early evaluate the number of grapevine berries by means of image analysis. Computers and Electronics in Agriculture 148: 19–28. https://doi.org/10.1016/j.compag.2018.02.021.

3. Canny, J.F. 1986. A computational approach to edge detection. IEEE Transactions on, PAMI 8: 679–698.

4. Cassia, Marcelo Tufaile, Rouverson Pereira, Carla da Silva, Segatto Strini Paixão, Rafael Scabello Bertonha, and Fábio Alexandre Cavichioli. 2014. Desgaste das facas do corte basal na qualidade da colheita mecanizada de cana-de-açúcar. Ciência Rural 44: 987–993. https://doi.org/10.1590/S0103-84782014000600006.

5. Confalonieri, R., M. Foi, R. Casa, S. Aquaro, E. Tona, M. Peterle, A. Boldini, et al. 2013. Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods. Computers and Electronics in Agriculture 96: 67–74. https://doi.org/10.1016/j.compag.2013.04.019.

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