Magalhães, I.A.L.; de Carvalho Júnior, O.A.; de Carvalho, O.L.F.; de Albuquerque, A.O.; Hermuche, P.M.; Merino, É.R.; Gomes, R.A.T.; Guimarães, R.F.
Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series. Remote Sens. 2022, 14, 4858.
https://doi.org/10.3390/rs14194858
AMA Style
Magalhães IAL, de Carvalho Júnior OA, de Carvalho OLF, de Albuquerque AO, Hermuche PM, Merino ÉR, Gomes RAT, Guimarães RF.
Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series. Remote Sensing. 2022; 14(19):4858.
https://doi.org/10.3390/rs14194858
Chicago/Turabian Style
Magalhães, Ivo Augusto Lopes, Osmar AbÃlio de Carvalho Júnior, Osmar Luiz Ferreira de Carvalho, Anesmar Olino de Albuquerque, Potira Meirelles Hermuche, Éder Renato Merino, Roberto Arnaldo Trancoso Gomes, and Renato Fontes Guimarães.
2022. "Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series" Remote Sensing 14, no. 19: 4858.
https://doi.org/10.3390/rs14194858
APA Style
Magalhães, I. A. L., de Carvalho Júnior, O. A., de Carvalho, O. L. F., de Albuquerque, A. O., Hermuche, P. M., Merino, É. R., Gomes, R. A. T., & Guimarães, R. F.
(2022). Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series. Remote Sensing, 14(19), 4858.
https://doi.org/10.3390/rs14194858