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 areasIn 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 DataIn IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 1365-1368). 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, 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, Article 4700, 1-21. Sun, X., Zhao, W., V. Maretto, R. & Persello, C.https://doi.org/10.3390/rs13224700Detecting clearcut deforestation employing deep learning methods and SAR time seriesIn 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 4520-4523). 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 dataIn 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 5401-5404). 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, 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 frameworkIn The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (pp. 487-493). 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, 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 CerradoIn 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings, Article 9323184 (pp. 1078-1081). 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 2023/2024
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 2022/2023
Adres
Universiteit Twente
Langezijds (gebouwnr. 19), kamer 1320
Hallenweg 8
7522 NH Enschede
Universiteit Twente
Langezijds 1320
Postbus 217
7500 AE Enschede
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