Thales Sehn Körting - researchr alias

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Viewing Publication 1 - 48 from 48

2022

Pacote 'Contraste': aplicação de técnicas de contraste baseado no uso e cobertura da terraDiego M. de Melo, Gisele Milare, Marielcio G. Lacerda, Gilberto Ribeiro de Queiroz, Thales Sehn Körting. geoinfo 2022: 293-298 [doi]

A High-Spatial Resolution Dataset and Few-shot Deep Learning Benchmark for Image ClassificationMateus de Souza Miranda, Lucas Fernando Alvarenga e Silva, Samuel Felipe dos Santos, Valdivino Alexandre de Santiago Júnior, Thales Sehn Körting, Jurandy Almeida. sibgrapi 2022: 19-24 [doi]

Identifying Precarious Settlements and Urban Fabric Typologies Based on GEOBIA and Data Mining in Brazilian Amazon CitiesBruno dos Santos, Carolina Moutinho Duque de Pinho, Gilberto Eidi Teramoto Oliveira, Thales Sehn Körting, Maria Isabel Sobral Escada, Silvana Amaral. remotesensing, 14(3):704, 2022. [doi]

FMASK algorithm applied to Landsat images: a study case in the region of Santarém, Pará, BrazilElton Vicente Escobar-Silva, Anielli Rosane De Souza, Maria Lucia Ferreira Barbosa, Cláudia Maria de Almeida, Liana Oighenstein Anderson, Gilberto Ribeiro de Queiroz, Thales Sehn Körting. geoinfo 2022: 347-352 [doi]

Near Real-Time Fire Detection and Monitoring in the MATOPIBA Region, BrazilMikhaela A. J. S. Pletsch, Thales Sehn Körting, Felipe Carraro Morita, Celso Henrique Leite Silva Junior, Liana Oighstein Anderson, Luiz E. O. C. Aragão. remotesensing, 14(13):3141, 2022. [doi]

2021

FrontmatterMaristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting. jidm, 12(4), 2021. [doi]

EditorialMaristela Terto de Holanda, Daniel Cardoso Moraes de Oliveira, Thales Sehn Körting. jidm, 12(4), 2021. [doi]

Utilizando o padrão SpatioTemporal Asset Catalog para visualização de dadosThais de Medeiros, Bruno dos Santos, Gilberto E. T. Oliveira, Thales Sehn Körting, Gilberto Ribeiro de Queiroz. geoinfo 2021: 264-269 [doi]

Classification of the water volume of dams using heterogeneous remote sensing images through a deep convolutional neural networkMateus de Souza Miranda, Renato S. Maximiano, Valdivino Alexandre de Santiago Júnior, Thales Sehn Körting, Leila M. G. Fonseca. geoinfo 2021: 179-188 [doi]

Deep Convolutional Neural Network for Classifying Satellite Images with Heterogeneous Spatial ResolutionsMateus de Souza Miranda, Valdivino Alexandre de Santiago Jr., Thales Sehn Körting, Rodrigo Leonardi, Moisés Laurence de Freitas. iccsa 2021: 519-530 [doi]

On a Data-Driven Approach for Detecting Disturbance in the Brazilian Savannas Using Time Series of Vegetation IndicesAlana Almeida de Souza, Lênio Soares Galvão, Thales Sehn Körting, Cláudio Aparecido de Almeida. remotesensing, 13(24):4959, 2021. [doi]

Detection of Agricultural Activity in Center Pivot Areas in Southeastern BrazilFelipe Rafael de Sá Menezes Lucena, Aline Casassola, Thales Sehn Körting, Leila Maria Garcia Fonseca, Hermann Johann Heinrich Kux. igarss 2021: 7043-7046 [doi]

Exploring Geostatistical Modeling and VisualizationTechniques of Uncertainties for Categorical Spatial DataCarlos A. Felgueiras, Jussara de Oliveira Ortiz, Eduardo Gerbi Camargo, Laércio Massaru Namikawa, Thales Sehn Körting. jidm, 12(4), 2021. [doi]

Pattern Recognition and Remote Sensing techniques applied to Land Use and Land Cover mapping in the Brazilian SavannahLeila M. G. Fonseca, Thales Sehn Körting, Hugo do Nascimento Bendini, Cesare Di Girolamo Neto, Alana Kasahara Neves, Anderson Reis Soares, Evandro Carrijo Taquary, Raian Vargas Maretto. prl, 148:54-60, 2021. [doi]

Automated cloud coverage analysis with Brazil Data CubeThainara Lima, Rômulo Marques, Ueslei Sutil, Cláudia Maria de Almeida, Cláudio C. Barbosa, Thales Sehn Körting, Gilberto Ribeiro de Queiroz. geoinfo 2021: 204-209 [doi]

Spatio-Temporal Deep Learning Approach to Map Deforestation in Amazon RainforestRaian Vargas Maretto, Leila M. G. Fonseca, Nathan Jacobs, Thales Sehn Körting, Hugo N. Bendini, Leandro Parente. lgrs, 18(5):771-775, 2021. [doi]

Environmental Drivers of Water Use for Caatinga Woody Plant Species: Combining Remote Sensing Phenology and Sap Flow MeasurementsRennan A. Paloschi, Desirée Marques Ramos, Dione J. Ventura, Rodolfo Souza, Eduardo Souza, Leonor Patricia Cerdeira Morellato, Rodolfo Luiz Bezerra Nóbrega, Ítalo Antônio Cotta Coutinho, Anne Verhoef, Thales Sehn Körting, Laura De Simone Borma. remotesensing, 13(1):75, 2021. [doi]

Simple Nonlinear Iterative Temporal ClusteringAnderson Reis Soares, Thales Sehn Körting, Leila M. G. Fonseca, Hugo N. Bendini. tgrs, 59(9):7669-7679, 2021. [doi]

2020

Applying A Phenological Object-Based Image Analysis (Phenobia) for Agricultural Land Classification: A Study Case in the Brazilian CerradoHugo N. Bendini, Leila M. G. Fonseca, Anderson Reis Soares, Philippe Rufin, Marcel Schwieder, Marcos A. Rodrigues, Raian Vargas Maretto, Thales Sehn Körting, Pedro J. Leitão, Ieda D. A. Sanches, Patrick Hostert. igarss 2020: 1078-1081 [doi]

EditorialAngelo Brayner, Maristela Holanda, Thales Sehn Körting. jidm, 11(2), 2020. [doi]

Spatial-temporal Analysis of active fire classified by INPE's Fire Risk Model in Brazil using Python languageGabriel M. da Silva, Bruno Vilhena Adorno, Gilberto Ribeiro de Queiroz, Thales Sehn Körting, Fabiano Morelli, Silvana Amaral, Yosio Edemir Shimabukuro. geoinfo 2020: 153-161 [doi]

Assessing Differentiation Between Pasture and Croplands Using Remote Sensing Image Time Series MetricsMarcos Antônio de Almeida Rodrigues, Hugo do Nascimento Bendini, Anderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca. igarss 2020: 168-171 [doi]

Identificação de pivôs centrais usando composições de bandas e um método rápido de Deep LearningDenis M. A. Eiras, Mikhaela A. J. S. Pletsch, Marcos Lima Rodrigues, Karine Reis Ferreira, Thales Sehn Körting. geoinfo 2020: 180-185 [doi]

Mapping Deforested Areas in the Cerrado Biome through Recurrent Neural NetworksB. M. Matosak, Raian Vargas Maretto, Thales Sehn Körting, Marcos Adami, Leila Maria Garcia Fonseca. igarss 2020: 1389-1392 [doi]

Circular Hough Transform and Balanced Random Forest to Detect Center PivotsMarcos Lima Rodrigues, Thales Sehn Körting, Gilberto Ribeiro de Queiroz. geoinfo 2020: 106-117 [doi]

Stmetrics: A Python Package for Satellite Image Time-Series Feature ExtractionAnderson Reis Soares, Hugo N. Bendini, Daiane V. Vaz, Tatiana D. T. Uehara, Alana Kasahara Neves, Sarah Lechler, Thales Sehn Körting, Leila M. G. Fonseca. igarss 2020: 2061-2064 [doi]

Land Cover Classification of an Area Susceptible to Landslides Using Random Forest and NDVI Time Series DataTatiana Dias Tardelli Uehara, Anderson Reis Soares, Renata Pacheco Quevedo, Thales Sehn Körting, Leila Maria Garcia Fonseca, Marcos Adami. igarss 2020: 1345-1348 [doi]

Aplicação do Modelo Aditivo Generalizado espacial para a modelagem da susceptibilidade a ocorrência de deslizamentosTatiana D. T. Uehara, Eduardo Gerbi Camargo, Camile Sothe, Thales Sehn Körting. geoinfo 2020: 110-115 [doi]

2019

FrontmatterAngelo Brayner, Maristela Holanda, Thales Sehn Körting. jidm, 10(1), 2019. [doi]

Detailed agricultural land classification in the Brazilian cerrado based on phenological information from dense satellite image time seriesHugo do Nascimento Bendini, Leila Maria Garcia Fonseca, Marcel Schwieder, Thales Sehn Körting, Philippe Rufin, Ieda Del'Arco Sanches, Pedro J. Leitão, Patrick Hostert. aeog, 82, 2019. [doi]

Comparing Phenometrics Extracted From Dense Landsat-Like Image Time Series for Crop ClassificationHugo do Nascimento Bendini, Leila Maria Garcia Fonseca, Marcel Schwieder, Thales Sehn Körting, Philippe Rufin, Ieda Del'Arco Sanches, Pedro J. Leitão, Patrick Hostert. igarss 2019: 469-472 [doi]

An Extensible and Easy-to-use Toolbox for Deep Learning Based Analysis of Remote Sensing ImagesRaian Vargas Maretto, Thales Sehn Körting, Leila Maria Garcia Fonseca. igarss 2019: 9815-9818 [doi]

Calibração relativa para extensão de assinaturas em série de imagens MODISNoeli A. P. Moreira, Thales Sehn Körting, Luciano Vieira Dutra, Emiliano Ferreira Castejon, Egidio Arai. geoinfo 2019: 230-236 [doi]

Hierarchical Classification of Brazilian Savanna Physiognomies Using Very High Spatial Resolution Image, Superpixel and GeobiaAlana Kasahara Neves, Thales Sehn Körting, Cesare Di Girolamo Neto, Anderson Reis Soares, Leila Maria Garcia Fonseca. igarss 2019: 3716-3719 [doi]

Using GOES-16 Time Series to characterize near real-time active fires in CerradoMikhaela A. J. S. Pletsch, Thales Sehn Körting, Felipe Carraro Morita, Fabiano Morelli, Olga Bittencourt, Paulo S. S. Victorino. geoinfo 2019: 66-76 [doi]

Potential of Using Sentinel-1 Data to Distinguish Targets in Remote Sensing ImagesMikhaela Aloísia Jéssie Santos Pletsch, Thales Sehn Körting, Willian Vieira de Oliveira, Ieda Del'Arco Sanches, Victor Velázquez Fernandez, Fábio Furlan Gama, Maria Isabel Sobral Escada. iccsa 2019: 563-576 [doi]

Classification algorithms comparison for landslide scarsTatiana Dias Tardelli Uehara, Sabrina Paes Leme Passos Correa, Renata Pacheco Quevedo, Thales Sehn Körting, Luciano Vieira Dutra, amilo Daleles Rennó. geoinfo 2019: 158-169 [doi]

2018

FrontmatterAngelo Brayner, Maristela Holanda, Roberto Willrich, Thales Sehn Körting, Celso A. S. Santos. jidm, 9(3):196, 2018. [doi]

2015

Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and AutoencodersWanderson Costa, Leila Maria Garcia Fonseca, Thales Sehn Körting. mldm 2015: 187-198 [doi]

Object-based image analysis for urban land cover classification in the city of Campinas - SP, BrazilDavid G. M. Franca, Rodolfo G. Lotte, Cláudia Maria de Almeida, Sacha M. O. Siani, Thales Sehn Körting, Leila M. G. Fonseca, Luiz T. da Silva. jurse 2015: 1-4 [doi]

Spectral Attributes Selection based on Data Mining for Remote Sensing Image ClassificationRaian Vargas Maretto, Thales Sehn Körting, Emiliano Ferreira Castejon, Leila Maria Garcia Fonseca, Rafael Santos. geoinfo 2015: 155-161 [doi]

Combining Time Series Features and Data Mining to Detect Land Cover patterns: a Case Study in Northern Mato Grosso State, BrazilAlana Kasahara Neves, Hugo N. Bendini, Thales Sehn Körting, Leila Maria Garcia Fonseca. geoinfo 2015: 174-185 [doi]

Improvements of the divide and segment method for parallel image segmentationAnderson Reis Soares, Thales Sehn Körting, Leila Maria Garcia Fonseca. geoinfo 2015: 222-232 [doi]

2014

Proposta de Sistema de Monitoramento da Sigatoka-Negra Baseado em Variáveis Ambientais Utilizando o TerraMA2Hugo N. Bendini, Wilson S. Moraes, Simone Costa, Eymar S. S. Lopes, Thales Sehn Körting, Leila Maria Garcia Fonseca. geoinfo 2014: 168-173 [doi]

Improvements in Sample Selection Methods for Image ClassificationThales Sehn Körting, Leila Maria Garcia Fonseca, Emiliano Ferreira Castejon, Laércio Massaru Namikawa. remotesensing, 6(8):7580-7591, 2014. [doi]

2013

GeoDMA - Geographic Data Mining AnalystThales Sehn Körting, Leila Maria Garcia Fonseca, Gilberto Câmara. gandc, 57:133-145, 2013. [doi]

The Divide and Segment Method for Parallel Image SegmentationThales Sehn Körting, Emiliano Ferreira Castejon, Leila Maria Garcia Fonseca. acivs 2013: 504-515 [doi]

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