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Baptiste Lafabrègue
Baptiste Lafabrègue
Associate Professor at University of Strasbourg
Verified email at unistra.fr
Title
Cited by
Cited by
Year
End-to-end deep representation learning for time series clustering: a comparative study
B Lafabregue, J Weber, P Gançarski, G Forestier
Data Mining and Knowledge Discovery 36 (1), 29-81, 2022
652022
Constrained distance based clustering for time-series: a comparative and experimental study
T Lampert, TBH Dao, B Lafabregue, N Serrette, G Forestier, B Crémilleux, ...
Data Mining and Knowledge Discovery 32, 1663-1707, 2018
442018
Constrained distance-based clustering for satellite image time-series
T Lampert, B Lafabregue, N Serrette, C Vrain, P Gançarski
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019
152019
Constrained distance based k-means clustering for satellite image time-series
T Lampert, B Lafabregue, P Gançarski
IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019
132019
Deep constrained clustering applied to satellite image time series
B Lafabregue, J Weber, P Gançarski, G Forestier
ECML/PKDD Workshop on Machine Learning for Earth Observation Data (MACLEAN), 2019
122019
Incremental constrained clustering with application to remote sensing images time series
B Lafabregue, P Gançarski, J Weber, G Forestier
2022 IEEE International Conference on Data Mining Workshops (ICDMW), 814-823, 2022
32022
FODOMUST-une plateforme de clustering collaboratif sous contraintes incrémental de séries temporelles
P Gançarski, B Lafabregue, AD Salaou, V Harrison
EGC, 507-514, 2020
32020
Grad Centroid Activation Mapping for Convolutional Neural Networks
B Lafabregue, J Weber, P Gançarski, G Forestier
2021 IEEE 33rd International Conference on Tools with Artificial …, 2021
12021
Clustering et apprentissage profond sous contraintes pour l'analyse de séries temporelles: application à l'analyse temporelle incrémentale en télédétection
B Lafabregue
Université de Haute Alsace-Mulhouse, 2021
12021
Learning from few labeled time series with segment-based self-supervised learning: application to remote-sensing
A Saget, B Lafabregue, A Cornuéjols, P Gançarski
Proceedings of SPAICE2024: The First Joint European Space Agency/IAA …, 2024
2024
Écrêter la valeur cible ou filtrer les données en maintenance prévisionnelle: exemple de C-MAPSS
N Mountasir, B Lafabregue, B Albert, N Lachiche
Extraction et Gestion des Connaissances (EGC'24), Dijon, France, 347-348, 2024
2024
Contrôle visuel de la qualité perçue par apprentissage automatique
N Mountasir, B Albert, B Lafabregue, N Lachiche
ORASIS 2023, 2023
2023
Deep Clustering Methods Study Applied to Satellite Images Time Series
B Lafabregue, A Puissant, J Weber, G Forestier
IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium …, 2022
2022
Constrained clustering and deep learning for time series analysis: with application to incremental temporal analysis for remote sensing
B Lafabregue
< bound method Organization. get_name_with_acronym of< Organization: TEL …, 2021
2021
Cybersecurity with Machine Learning for industrial networks
SDF Théoleyre, B Lafabregue, T Gaberan
Clustering contraint par apprentissage profond appliqué aux séries temporelles d’images satellites
B Lafabregue, J Weber, P Gançarski, G Forestier
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