@InProceedings{AdeuFerrAndrSant:2019:EvGrSe,
author = "Adeu, Rodrigo S. S. and Ferreira, Karine Reis and Andrade, Pedro
Ribeiro de and Santos, Lorena",
affiliation = "Embraer and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)}",
title = "Evaluating growing self-organizing maps for satellite image time
series clustering",
booktitle = "Anais... do 20º Simp{\'o}sio Brasileiro de Geoinform{\'a}tica",
year = "2019",
editor = "Lisboa Filho, Jugurta and Monteiro, Antonio Miguel Vieira",
organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 20. (GEOINFO)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "geoinformatica.",
abstract = "In recent years, analysis of time series extracted from Earth
observation satellite images has been widely used to produce land
use and cover information. In time series analysis, clustering is
a common technique performed to discover patterns on data sets.
Self-Organizing Maps (SOM) neural network is a suitable method for
such task. However, a critical limitation of SOM is that its map
structure size must be predetermined. This limitation has been
addressed by Growing SOM method. This paper presents an ongoing
work on evaluating Growing SOM for Earth observation satellite
image time series clustering.",
conference-location = "S{\~a}o Jos{\'e} dos Campos",
conference-year = "11 -13 nov. 2019",
issn = "2179-4847",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGPDW34R/3UFECJL",
url = "http://urlib.net/ibi/8JMKD3MGPDW34R/3UFECJL",
targetfile = "243-248.pdf",
urlaccessdate = "21 maio 2024"
}