Expertises
Engineering & Materials Science
# Long Short-Term Memory
# Remote Sensing
# Satellites
# Time Series
Earth & Environmental Sciences
# Detection
# Land Cover
# Learning
# Remote Sensing
Verbonden aan
Publicaties
Recent
Boakye, A. S.
, Huesca Martinez, M.
, & Paris, C. (2023).
A study on the impact of the spatial and spectral resolution on plant species richness in Mediterranean regions using optical remote sensing data. In L. Bruzzone, & F. Bovolo (Eds.),
Image and Signal Processing for Remote Sensing XXIX (Vol. 12733). SPIE.
https://doi.org/10.1117/12.2679116
Paris, C., Martinez-Sanchez, L., Velde, M. V. D., Sharma, S., Sedona, R., & Cavallaro, G. (2023).
Accuracy assessment of land-use-land-cover maps: the semantic gap between in situ and satellite data. In L. Bruzzone, & F. Bovolo (Eds.),
Image and Signal Processing for Remote Sensing XXIX (Vol. 12733). SPIE.
https://doi.org/10.1117/12.2679433
Appel, F., Bach, H., Migdall, S., Koubarakis, M., Stamoulis, G., Bilidas, D., Pantazi, D. A., Bruzzone, L.
, Paris, C., & Weikmann, G. (2023).
ExtremeEarth: Managing water availability for crops using Earth Observation and machine learning. In
Proceedings 26th International Conference on Extending Database Technology ( EDBT 2023 ) (3 ed., Vol. 26, pp. 749-756). (Advances in Database Technology - EDBT; Vol. 26).
https://doi.org/10.48786/edbt.2023.62
Tian, L., Sedona, R., Mozaffari, A., Kreshpa, E.
, Paris, C., Riedel, M., Schultz, M. G., & Cavallaro, G. (2023).
End-to-end process orchestration of Earth Observation data workflows with apache airflow on high performance computing. In
IGARSS 2023: 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 711-714). Article 10283416 IEEE.
https://doi.org/10.1109/IGARSS52108.2023.10283416
Sedona, R., Ebert, J.
, Paris, C., Riedel, M., & Cavallaro, G. (2023).
Enhancing training set through multi-temporal attention analysis in transformers for multi-year land cover mapping. In
IGARSS 2023: 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 5411-5414). Article 10283284 IEEE.
https://doi.org/10.1109/IGARSS52108.2023.10283284
Abbas, A., Linardi, M., Vareille, E., Christophides, V.
, & Paris, C. (2023).
Towards Explainable AI4EO: An Explainable Deep Learning Approach for Crop Type Mapping using Satellite Images Time Series. In
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 1088-1091). Article 10283125 IEEE.
https://doi.org/10.1109/IGARSS52108.2023.10283125
Persello, C.
, Grift, J.
, Fan, X.
, Paris, C., Hänsch, R.
, Koeva, M.
, & Nelson, A. (2023).
AI4SmallFarms: A data set for crop field delineation in Southeast Asian smallholder farms.
IEEE geoscience and remote sensing letters,
20, 1-5. Article 2505705.
https://doi.org/10.1109/LGRS.2023.3323095
Weikmann, G., Marinelli, D.
, Paris, C., Migdall, S., Gleisberg, E., Appel, F., Bach, H., Dowling, J., & Bruzzone, L. (2023).
Multi-year mapping of water demand at crop level: An end-to-end workflow based on high-resolution crop type maps and meteorological data.
IEEE Journal of selected topics in applied earth observations and remote sensing,
16, 6758-6775. Advance online publication.
https://doi.org/10.1109/JSTARS.2023.3294107
Paris, C., Bruzzone, L., Bovolo, F., Maggiolo, L., Gamba, P., Moser, G., Pierantoni, G., Podsiadlo, I., Solarna, D., Sorriso, T., Zanetti, M., & Meshkini, K. (2022).
ESA CCI High Resolution Land Cover: Methodology and EO Data Processing Chain. Abstract from ESA Living Planet Symposium 2022, Bonn, Germany.
Sedona, R.
, Paris, C., Tian, L., Riedel, M., & Cavallaro, G. (2022).
An Automatic Approach for the Production of a Time Series of Consistent Land-Cover Maps Based on Long-Short Term Memory. In
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 203-206). Article 9883655 IEEE.
https://doi.org/10.1109/IGARSS46834.2022.9883655
Migdall, S., Dotzler, S., Gleisberg, E., Appel, F., Muerth, M., Bach, H., Weikmann, G.
, Paris, C., Marinelli, D., & Bruzzone, L. (2022).
Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling.
Engineering proceedings,
9(1), Article 42.
https://doi.org/10.3390/engproc2021009042
Marinelli, D.
, Paris, C., & Bruzzone, L. (2022).
An approach based on Deep Learning for tree species classification in LiDAR data acquired in mixed forest.
IEEE geoscience and remote sensing letters,
19, Article 7004305.
https://doi.org/10.1109/LGRS.2022.3181680
Paris, C., Gasparella, L., & Bruzzone, L. (2022).
A Scalable High-Performance Unsupervised System for Producing Large-Scale HR Land Cover Maps: The Italian country case study.
IEEE Journal of selected topics in applied earth observations and remote sensing,
15, 9146-9159.
https://doi.org/10.1109/JSTARS.2022.3209902
Paris, C., Kotowska, M. M., Erasmi, S.
, & Schlund, M. (2022).
A novel approach for environmental monitoring based on the integration of multi-temporal multi-source Earth Observation data and field surveys in a spatio-temporal framework. In
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 5897-5900). IEEE.
https://doi.org/10.1109/igarss46834.2022.9884130
Marinelli, D.
, Paris, C., & Bruzzone, L. (2022).
A triangulation-based technique for tree-top detection in heterogeneous forest structures using high density LiDAR data.
IEEE geoscience and remote sensing letters,
19. Advance online publication.
https://doi.org/10.1109/LGRS.2021.3115470
Paris, C., Orlandi, L., & Bruzzone, L. (2022).
An interactive strategy for the training set definition based on active self-paced learning implemented on a cloud-computing platform.
IEEE geoscience and remote sensing letters,
19, 1-5. Advance online publication.
https://doi.org/10.1109/LGRS.2021.3114611
Koubarakis, M., Stamoulis, G., Bilidas, D., Ioannidis, T., Mandilaras, G., Pantazi, D-A., Papadakis, G., Vlassov, V., Payberah, A. H., Wang, T., Sheikholeslami, S., Hagos, D. H., Bruzzone, L.
, Paris, C., Weikmann, G., Marinelli, D., Eltoft, T., Marinoni, A., Kraemer, T., ... Cziferszky, A. (2021).
Artificial Intelligence and big data technologies for Copernicus data: The EXTREMEEARTH project. In P. Soille, S. Loekken, & S. Albani (Eds.),
Proceedings of the 2021 conference on Big Data from Space (pp. 9-12). Publications Office of the European Union.
https://iris.unitn.it/handle/11572/330197
Migdall, S., Dotzler, S., Miesgang, C., Appel, F., Muerth, M., Bach, H., Weikmann, G.
, Paris, C., Marinelli, D., & Bruzzone, L. (2021).
Water Stress Assessment in Austria based on Deep Learning and Crop Growth Modelling. In
Proceedings of the 2021 conference on Big Data from Space (pp. 69-72). Publications Office of the European Union.
https://iris.unitn.it/handle/11572/330202
Weikmann, G.
, Paris, C., & Bruzzone, L. (2021).
Multi-year crop type mapping using pre-Trained deep long-short term memory and Sentinel 2 image time series. In L. Bruzzone, F. Bovolo, & J. A. Benediktsson (Eds.),
Image and Signal Processing for Remote Sensing XXVII Article 118620O (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11862). SPIE.
https://doi.org/10.1117/12.2600559
Podsiadlo, I.
, Paris, C., & Bruzzone, L. (2021).
An Approach Based on Low Resolution Land-Cover-Maps and Domain Adaptation to Define Representative Training Sets at Large Scale. In
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 313-316). IEEE.
https://doi.org/10.1109/IGARSS47720.2021.9553498
Sedona, R.
, Paris, C., Cavallaro, G., Bruzzone, L., & Riedel, M. (2021).
A high-performance multispectral adaptation GAN for harmonizing dense time series of Landsat-8 and Sentinel-2 images.
IEEE Journal of selected topics in applied earth observations and remote sensing,
14, 10134 - 10146.
https://doi.org/10.1109/jstars.2021.3115604
Weikmann, G.
, Paris, C., & Bruzzone, L. (2021).
TimeSen2Crop: A million labeled samples dataset of Sentinel 2 image time series for crop-type classification.
IEEE Journal of selected topics in applied earth observations and remote sensing,
14, 4699-4708. Article 9408357.
https://doi.org/10.1109/JSTARS.2021.3073965
Hagos, D. H., Kakantousis, T., Vlassov, V., Sheikholeslami, S., Wang, T., Dowling, J.
, Paris, C., Marinelli, D., Weikmann, G., Bruzzone, L., Khaleghian, S., Krmer, T., Eltoft, T., Marinoni, A., Pantazi, D-A., Stamoulis, G., Bilidas, D., Papadakis, G., Mandilaras, G., ... Cziferszky, A. (2021).
ExtremeEarth meets satellite data from space.
IEEE Journal of selected topics in applied earth observations and remote sensing,
14, 9038-9063.
https://doi.org/10.1109/JSTARS.2021.3107982
Troumpoukis, A., Konstantopoulos, S., Mouchakis, G., Prokopaki-Kostopoulou, N.
, Paris, C., Bruzzone, L., Pantazi, D. A., & Koubarakis, M. (2020).
GeoFedBench: A benchmark for federated GeoSPARQL query processors.
CEUR workshop proceedings,
2721, 229-232.
Paris, C., Weikmann, G., & Bruzzone, L. (2020).
A study of the robustness of the long short-term memory classifier to cloudy time series of multispectral images. In
SPIE Remote Sensing 2020 (pp. 1-10). (Proceedings of SPIE - the international society for optical engineering; Vol. 11533).
https://doi.org/10.1117/12.2574383
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Master
Vakken Collegejaar 2022/2023
Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
(gebouwnr. 19), kamer 1121
Hallenweg 8
7522NH Enschede
Postadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
1121
Postbus 217
7500 AE Enschede