Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning
- DOI
- 10.1109/mgrs.2022.3219935
- Published
- 2022
- Container
- IEEE geoscience and remote sensing magazine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/mgrs.2022.3219935,
title = {Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning},
author = {Ronny Hansch and Claudio Persello and Gemine Vivone and Javiera Castillo Navarro and Alexandre Boulch and Sébastien Lefèvre and Bertrand Le Saux},
year = {2022},
journal = {IEEE geoscience and remote sensing magazine},
doi = {10.1109/mgrs.2022.3219935},
url = {https://doi.org/10.1109/mgrs.2022.3219935}
}RIS
TY - JOUR TI - Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning AU - Ronny Hansch AU - Claudio Persello AU - Gemine Vivone AU - Javiera Castillo Navarro AU - Alexandre Boulch AU - Sébastien Lefèvre AU - Bertrand Le Saux PY - 2022 JO - IEEE geoscience and remote sensing magazine DO - 10.1109/mgrs.2022.3219935 UR - https://doi.org/10.1109/mgrs.2022.3219935 ER -
APA
Hansch, R., Persello, C., Vivone, G., Navarro, J. C., Boulch, A., Lefèvre, S., & Saux, B. L. (2022). Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning. IEEE geoscience and remote sensing magazine. https://doi.org/10.1109/mgrs.2022.3219935
Source records
- hal · retrieved 2026-11-10T10:21:49.262Z