dr. C. Paris (Claudia)

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