Langezijds

dr. R. Vargas Maretto (Raian)

Universitair docent
ITC-EOS
Langezijds 1320
r.v.maretto@utwente.nl
+31534894712
Visitekaartje

Expertises

  • Earth and Planetary Sciences

    • Cerrado
    • Cartography
    • Learning
    • Biome
    • Map
    • Model
    • Vegetation

  • Computer Science

    • Models

Organisaties

Publicaties

2024

Feature-guided deep learning model for mapping deprived areas (2024)In 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. IEEE. Filho, P. S., Tareke, B., Persello, C., Kuffer, M., Maretto, R., Abascal, A., Wang, J. & MacHado, R.https://doi.org/10.1109/MIGARS61408.2024.10544988

2023

Investigating Sar-Optical Deep Learning Data Fusion to Map the Brazilian Cerrado Vegetation with Sentinel Data (2023)In IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 1365-1368) (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2023-July). IEEE. Filho, P. S., Persello, C., Maretto, R. V. & MacHado, R.https://doi.org/10.1109/IGARSS52108.2023.10282190

2022

Mapping Deforestation in Cerrado Based on Hybrid Deep Learning Architecture and Medium Spatial Resolution Satellite Time Series (2022)Remote sensing, 14(1). Article 209. Matosak, B. M., Fonseca, L. M. G., Taquary, E. C., Maretto, R. V., Bendini, H. D. N. & Adami, M.https://doi.org/10.3390/rs14010209

2021

Building polygon extraction from aerial images and digital surface models with a frame field learning framework (2021)Remote sensing, 13(22), 1-21. Article 4700. Sun, X., Zhao, W., V. Maretto, R. & Persello, C.https://doi.org/10.3390/rs13224700Detecting clearcut deforestation employing deep learning methods and SAR time series (2021)In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 4520-4523) (IEEE International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021). IEEE. Taquary, E. C., Fonseca, L. M. G., Maretto, R. V., Bendini, H. N., Matosak, B. M., Sant'Anna, S. J. S. & Mura, J. C.https://doi.org/10.1109/igarss47720.2021.9554383Exploring a deep convolutional neural network and GEOBIA for automatic recognition of Brazilian Palm Swamps (Veredas) using Sentinel-2 optical data (2021)In 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 5401-5404) (IEEE International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021). IEEE. Bendini, H. N., Fonseca, L. M. G., Maretto, R. V., Matosak, B. M., Taquary, E. C., Haidar, R. F. & Valeriano, D. d. M.https://doi.org/10.1109/igarss47720.2021.9554050Pattern recognition and remote sensing techniques applied to land use and land cover mapping in the Brazilian Savannah (2021)Pattern recognition letters, 148, 54-60. Fonseca, L. M. G., Körting, T. S., Bendini, H. N., Girolamo Neto, C. D., Neves, A. K., Soares, A. R., Taquary, E. C. & Maretto, R. V.https://doi.org/10.1016/j.patrec.2021.04.028Building outline extraction from aerial imagery and digital surface model with a frame field learning framework (2021)In The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 487-493) (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives). International Society for Photogrammetry and Remote Sensing (ISPRS). Sun, X., Zhao, W., Maretto, R. V. & Persello, C.https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-487-2021Spatio-temporal deep learning approach to map deforestation in Amazon rainforest (2021)IEEE geoscience and remote sensing letters, 18(5), 771-775. Maretto, R. V., Fonseca, L. M. G., Jacobs, N., Korting, T. S., Bendini, H. N. & Parente, L. L.https://doi.org/10.1109/LGRS.2020.2986407

2020

Applying a phenological object-based image analysis (phenobia) for agricultural land classification: A study case in the Brazilian Cerrado (2020)In 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings (pp. 1078-1081). Article 9323184 (Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2020). IEEE. Bendini, H. N., Fonseca, L. M. G., Soares, A. R., Rufin, P., Schwieder, M., Rodrigues, M. A., Maretto, R. V., Korting, T. S., Leitao, P. J., Sanches, I. D. A. & Hostert, P.https://doi.org/10.1109/IGARSS39084.2020.9323184

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Vakken collegejaar 2024/2025

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.

Vakken collegejaar 2023/2024

Adres

Universiteit Twente

Langezijds (gebouwnr. 19), kamer 1320
Hallenweg 8
7522 NH Enschede

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