Publications

[1] Special session at LPS 2022, Representation learning in remote sensing: from unsupervised to self- and meta-learning.

[2] Invited session of the ISPRS 2022, Unsupervised and weakly supervised deep learning for EO. 

[3] Special session at IGARSS 2023, Representation learning for remote sensing.

[4] Special session at LPS 2025, Foundation Models for Earth Observation.

[1] 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.

[2] 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.

[3] 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.

[4] 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).

[5] C.O. Dumitru, R. Kuzu, L. Bagaglini, and F. Santarelli, “Building Anomaly Detection with Self-supervised Learning. Case Study: The City of Bucharest, Romania“, URBIS24 Workshop, Frascati, Italy, 16-18 September 2024 (poster).

[1] R. S. Kuzu, O. Antropov, M. Molinier, C. O. Dumitru, S. Saha and X. X. Zhu, Forest Disturbance Detection via Self-supervised and Transfer Learning with Sentinel-1&2 Images,IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)

[2] 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).

[3] 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).