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GitHub - AI4LUC
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Brazil

Biography

Mateus de Souza Miranda is a researcher and developer in deep learning for image processing field, with regard to semantic segmentation and contextual classification. Also, He has been working on remote sensing imagery processing in order to classify types of land use and land cover in the Cerrado biome. Mateus received B.Sc. in Computer Science Teaching from the Federal Institute of Tocantins, with a focus on teaching and research in computer science, and M.Sc. in Applied Computing with a focus on Deep Learning scopes for image processing, from the National Institute for Space Research (INPE). At the present, he is a Ph.D. researcher in Applied Computing at the INPE.

Activities

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Funding (3)

Pesquisa e Desenvolvimento em Métodos de Inteligência Artificial para Análise de Grandes Volumes de Dados Observacionais

2023-04 to 2027-03 | Grant
Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brasília, BR)
Source: Self-asserted source
Miranda, M.

Deep convolutional neural network for classifying satellite images with heterogeneous spatial resolutions

2021-10 to 2021-10 | Award
The international Conference on Computational Science and Its Applications (Potenza, IT)
URL: https://doi.org/10.1007/978-3-030-87007-2_37
Source: Self-asserted source
Miranda, M.

AI4LUC: PIXEL-BASED CLASSIFICATION OF LAND USE AND LAND COVER VIA DEEP LEARNING AND A CERRADO IMAGE DATASET

2021-03 to 2023-02 | Grant
Coordenação de Aperfeicoamento de Pessoal de Nível Superior (Brasília, BR)
Source: Self-asserted source
Miranda, M.

Works (5)

AI4LUC: deep learning and automated mask labelling to support land use and land cover mapping in the Cerrado biome

Remote Sensing Letters
2024-08-02 | Journal article
DOI: 10.1080/2150704X.2024.2382845
Contributors: Mateus de Souza Miranda; Valdivino Alexandre de Santiago Júnior; Thales Sehn Körting; Erison Carlos dos Santos Monteiro; Jadson Queiroz da Silva
Source: check_circle
Crossref

A High-Spatial Resolution Dataset and Few-shot Deep Learning Benchmark for Image Classification

2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)
2022-10-24 | Journal article
DOI: 10.1109/sibgrapi55357.2022.9991746
Contributors: Mateus De Souza Miranda; Lucas Fernando Alvarenga e Silva; Samuel Felipe Dos Santos; Valdivino Alexandre de Santiago Junior; Thales Sehn Korting; Jurandy Almeida
Source: Self-asserted source
Miranda, M.

Deep Convolutional Neural Network for Classifying Satellite Images with Heterogeneous Spatial Resolutions

Computational Science and Its Applications – ICCSA 2021
2021 | Book chapter | Author
DOI: 10.1007/978-3-030-87007-2_37
Part of ISBN: 9783030870065
Part of ISBN: 9783030870072
Part of ISSN: 0302-9743
Part of ISSN: 1611-3349
Contributors: Miranda, M.; Valdivino Alexandre de Santiago Júnior; Thales Sehn Körting; Rodrigo Leonardi; Moisés Laurence de Freitas Lima Junior
Source: Self-asserted source
Miranda, M.
grade
Preferred source (of 2)‎

Classification of the water volume of dams using heterogeneous remote sensing images through a deep convolutional neural network

SIMPÓSIO BRASILEIRO DE GEOINFORMÁTICA
2021-02-12 | Conference paper
Contributors: Miranda, M.; Maximiano, R.; Santiago Júnior, V.A.; Körting, T.; Fonseca, L.M.
Source: Self-asserted source
Miranda, M.

BRAIN STUDANTS GAMES E REALIDADE VIRTUAL E MISTURADA COMO METODOLOGIA ATIVA NO ENSINO DE CIÊNCIAS PARA ALUNOS DO 6º ANO DO ENSINO FUNDAMENTAL EM ARAGUATINS, TO

TÍTULO DOS ANAIS: INTEGRAR E INOVAR SABERES PARA A DEMOCRATIZAÇÃO DO CONHECIMENTO
2018 | Journal article
DOI: 10.31692/2358-9728.vcointerpdvl.2018.00043
Contributors: Mateus de Souza Miranda; Maristela Tavares Gonçalves
Source: Self-asserted source
Miranda, M.
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