| # | Publication | Year | Download |
|---|---|---|---|
| 1 | José María Tárraga, Maria Piles, Gustau Camps-Valls Learning drivers of climate-induced human migrations with Gaussian processes Presented at NeurIPS 2020 Workshop on Machine Learning for the Developing World | 2020 | 2011.08901 |
| 2 | Ioannis Papoutsis, Alkyoni Baglatzi, Souzana Touloumtzi, Markus Reichstein, Nuno Carvalhais, Fabian Gans, Gustau Camps-Valls, Maria Piles, Theofilos Kakantousis, Jim Dowling, Manolis Koubarakis, Dimitris Bilidas, Despina-Athanasia Pantazi, George Stamoulis, Christophe Demange, Leo-Gad Journel, Marco Bianchi, Chiara Gervasi, Alessio Rucci, Ioannis Tsampoulatidis, Eleni Kamateri, Tarek Habib, Alejandro Diaz Bolivar, Zisoula Ntasiou, Anastasios Paschalis DEEPCUBE: EXPLAINABLE AI PIPELINES FOR BIG COPERNICUS DATA Proceedings of the 2021 conference on Big Data from Space (BiDS’21) | 2021 | |
| 3 | Nikolaos Ioannis Bountos, Ioannis Papoutsis, Dimitrios Michail, Nantheera Anantrasirichai Self-Supervised Contrastive Learning for Volcanic Unrest Detection Published in IEEE Geoscience and Remote Sensing Letters (Early Access) | 2021 | |
| 4 | Ioannis Prapas, Spyros Kondylatos, Ioannis Papoutsis, Gustau Camps-Valls, Michele Ronco, Miguel-Ángel Fernández-Torres, Maria Piles Guillem, Nuno Carvalhais Deep Learning Methods for Daily Wildfire Danger Forecasting Accepted to the workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response at the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) | 2021 | 2111.02736 |
| 5 | Dimitris Sykas, Ioannis Papoutsis, Dimitrios Zografakis Sen4AgriNet: A Harmonized Multi-Country, Multi-Temporal Benchmark Dataset for Agricultural Earth Observation Machine Learning Applications IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 5830-5833 DOI: https://doi.org/10.1109/IGARSS47720.2021.9553603 | 2021 | |
| 6 | Ioannis Papoutsis, Nikolaos-Ioannis Bountos, Angelos Zavras, Dimitrios Michail, Christos Tryfonopoulos Benchmarking and scaling of deep learning models for land cover image classification Open access: https://arxiv.org/abs/2111.09451 | 2021 | |
| 7 | José María Tárraga, Michele Ronco, Maria Teresa Miranda Espinosa, Maria Piles, Eva Sevillano Marco, Jordi Muñoz, Gustau Camps-Valls Climate-Induced Displacement with Explainable Machine Learning Models AGU American Geophysical Union, New Orleans LA USA & Online, 13-17 December 2021, https://www.agu.org/Fall-Meeting 2021 | 2021 | |
| 8 | N. I. Bountos, D. Michail and I. Papoutsis, Learning From Synthetic InSAR With Vision Transformers: The Case of Volcanic Unrest Detection, in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-12, 2022, Art no. 4509712, doi: https://doi.org/10.1109/TGRS.2022.3180891 | 2022 | |
| 9 | Dimitrios Sykas, Maria Sdraka, Dimitrios Zografakis, Ioannis Papoutsis A Sentinel-2 Multiyear, Multicountry Benchmark Dataset for Crop Classification and Segmentation With Deep Learning IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 15, p. 3323 - 3339 DOI: https://doi.org/10.1109/JSTARS.2022.3164771 | 2022 | |
| 10 | Ronco, M., Prapas, I., Kondylatos, S., Papoutsis, I., Camps-Valls, G., Fernández-Torres, M.-Á., Piles Guillem, M., and Carvalhais, N.: Explainable deep learning for wildfire danger estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11787, https://doi.org/10.5194/egusphere-egu22-11787, 2022. | 2022 | |
| 11 | M. Fernández-Torres, M. Ronco, V. Benson, C. Requena, M. Mahecha, G. Camps-Valls, Explaining Deep Learning Models for Earth Surface Forecasting, Living Planet Symposium, 23-27 May 2022, Bonn, Germany 2022 | 2022 | |
| 12 | José María Tárraga et al., Inspecting the link between climate and human displacement with Explainable AI and Causal inference, EGU General Assembly, Geophysical Research Abstracts, Hybrid, 23-27 May 2022 Vol. 24 2022, https://doi.org/10.5194/egusphere-egu22-11200 | 2022 | |
| 13 | N.I. Bountos, I. Papoutsis, D. Michail, A. Karavias, P. Elias, I. Parcharidis, Hephaestus: A large scale multitask dataset towards InSAR understanding, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) EarthVision, 2022, https://doi.org/10.48550/arXiv.2204.09435 | 2022 | |
| 14 | Claire Robin, Christian Requena-Mesa, Vitus Benson, Lazaro Alonso, Jeran Poehls, Nuno Carvalhais, Markus Reichstein, Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs, Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop at NeurIPS 2022, https://doi.org/10.48550/arXiv.2210.13648 | 2022 | |
| 15 | S. Kondylatos, I. Prapas, M. Ronco, I. Papoutsis, G. Camps-Valls, M. Piles, M. Fernández-Torres, N. Carvalhais, Wildfire Danger Prediction and Understanding With Deep Learning, AGU Geophysical Research Letters, https://doi.org/10.1029/2022GL099368 | 2022 | |
| 16 | M. Ioannidou, A. Koukos, V. Sitokonstantinou, I. Papoutsis, C. Kontoes, Assessing the Added Value of Sentinel-1 PolSAR Data for Crop Classification, Remote Sens. 2022, 14(22), 5739; https://doi.org/10.3390/rs14225739 | 2022 |
