Welkom...

dr. C. Paris (Claudia)

Universitair docent

Expertises

Engineering & Materials Science
Long Short-Term Memory
Remote Sensing
Satellites
Time Series
Earth & Environmental Sciences
Detection
Land Cover
Learning
Remote Sensing

Publicaties

Recent
Sedona, R. , Paris, C., Ebert, J., Riedel, M., & Cavallaro, G. (2023). Toward the production of spatiotemporally consistent annual land cover maps using Sentinel-2 time series. IEEE geoscience and remote sensing letters, 20, 1-5. Article 2505805. Advance online publication. https://doi.org/10.1109/LGRS.2023.3329428
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). Article 127330W 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). Article 127330M 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
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. 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
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.

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Verbonden aan Opleidingen

Master

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

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