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Sylvain Lobry
Sylvain Lobry
Associate professor, Université Paris Cité
Zweryfikowany adres z u-paris.fr - Strona główna
Tytuł
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Cytowane przez
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RSVQA: Visual question answering for remote sensing data
S Lobry, D Marcos, J Murray, D Tuia
IEEE Transactions on Geoscience and Remote Sensing 58 (12), 8555-8566, 2020
2252020
Half a percent of labels is enough: Efficient animal detection in UAV imagery using deep CNNs and active learning
B Kellenberger, D Marcos, S Lobry, D Tuia
IEEE Transactions on Geoscience and Remote Sensing 57 (12), 9524-9533, 2019
1392019
A deep learning framework for matching of SAR and optical imagery
LH Hughes, D Marcos, S Lobry, D Tuia, M Schmitt
ISPRS Journal of Photogrammetry and Remote Sensing 169, 166-179, 2020
1212020
Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data
S Srivastava, JE Vargas Munoz, S Lobry, D Tuia
International Journal of Geographical Information Science 34 (6), 1117-1136, 2020
932020
Correcting rural building annotations in OpenStreetMap using convolutional neural networks
JE Vargas-Muñoz, S Lobry, AX Falcão, D Tuia
ISPRS journal of photogrammetry and remote sensing 147, 283-293, 2019
702019
Scale equivariance in CNNs with vector fields
D Marcos, B Kellenberger, S Lobry, D Tuia
arXiv preprint arXiv:1807.11783, 2018
642018
Prompt-RSVQA: Prompting visual context to a language model for remote sensing visual question answering
C Chappuis, V Zermatten, S Lobry, B Le Saux, D Tuia
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
612022
RSVQA meets BigEarthNet: a new, large-scale, visual question answering dataset for remote sensing
S Lobry, B Demir, D Tuia
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1218 …, 2021
472021
Shrub decline and expansion of wetland vegetation revealed by very high resolution land cover change detection in the Siberian lowland tundra
RÍ Magnússon, J Limpens, D Kleijn, K van Huissteden, TC Maximov, ...
Science of the Total Environment 782, 146877, 2021
432021
Contextual semantic interpretability
D Marcos, R Fong, S Lobry, R Flamary, N Courty, D Tuia
Proceedings of the Asian Conference on Computer Vision, 2020
362020
Learning multi-label aerial image classification under label noise: A regularization approach using word embeddings
Y Hua, S Lobry, L Mou, D Tuia, XX Zhu
IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020
342020
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs
D Marcos, S Lobry, D Tuia
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW …, 2019
332019
Wasserstein adversarial regularization for learning with label noise
K Fatras, BB Damodaran, S Lobry, R Flamary, D Tuia, N Courty
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 7296 …, 2021
322021
Multitemporal SAR image decomposition into strong scatterers, background, and speckle
S Lobry, L Denis, F Tupin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2016
282016
How to find a good image-text embedding for remote sensing visual question answering?
C Chappuis, S Lobry, B Kellenberger, BL Saux, D Tuia
arXiv preprint arXiv:2109.11848, 2021
272021
Visual question answering on remote sensing images
S Lobry, D Tuia
Advances in Machine Learning and Image Analysis for GeoAI, 237-254, 2024
212024
Language transformers for remote sensing visual question answering
C Chappuis, V Mendez, E Walt, S Lobry, B Le Saux, D Tuia
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022
162022
Better generic objects counting when asking questions to images: A multitask approach for remote sensing visual question answering
S Lobry, D Marcos, B Kellenberger, D Tuia
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020
142020
Interpretable scenicness from sentinel-2 imagery
A Levering, D Marcos, S Lobry, D Tuia
IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020
102020
Deep learning models to count buildings in high-resolution overhead images
S Lobry, D Tuia
2019 Joint Urban Remote Sensing Event (JURSE), 1-4, 2019
92019
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