The list of publications related to the project.
 Special session at LPS 2022, Representation learning in remote sensing: from unsupervised to self- and meta-learning.
 Invited session of the ISPRS 2022, Unsupervised and weakly supervised deep learning for EO.
 Special session at IGARSS 2023, Representation learning for remote sensing.
 R. Kuzu, Y. Wang, O. Dumitru, L. Bagaglini, G. Pasquali, F. Santarelli, F. Trillo, S. Saha, and X. Zhu, An Unsupervised Anomaly Detection Problem in Urban InSAR-PSP Long Time-series, EGU 2023, Vienna, 23-28 April 2023.
 O. Antropov, M. Molinier, R. Kuzu, L. Hughes, M. Rußwurm, D. Tuia, O. Dumitru, S. Ge, S. Saha, X. Zhu, Semi-Supervised Deep Learning Representations in Earthe Observation Based Forest Management, IGRASS 2023, Pasadena, 16-21 July 2023.
 M. Rußwurm, L. Hughes, G. Pasquali, O. Dumitru, D. Tuia, Detection of Settlements in Tanzania and Mozambique by Many Regional Few-Shot Models, IGRASS 2023, Pasadena, 16-21 July 2023.
 C.O. Dumitru, R. Kuzu, L. Hughes, M. Russwurm, D. Tuia, O. Antropov, M. Molinier, G. Pasquali, L. Bagaglini, A. Rösel, and X.X. Zhu, “RepreSent: Non-supervised Representation Learning for Sentinels”, Neue Perspektiven der Erdbeobachtung Symposium, Bonn, Germany, 26-28 June 2023 (poster).
 R. Kuzu , L. Bagaglini, Y. Wang, C.O. Dumitru, N.A. Ali Braham, G. Pasquali, F. Santarelli, F. Trillo, S. Saha, and X. Zhu, Automatic Detection of Building Displacements through Unsupervised Learning-based Deep Feature Representations from InSAR Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023).
 Y. Wang, C. Albrecht, N. Ait Ali Braham, L. Mou and X. Zhu, Self-Supervised Learning in Remote Sensing: A Review, IEEE Geoscience and Remote Sensing Magazine (2022).