Land cover classification via multitemporal spatial data by deep recurrent neural networks D Ienco, R Gaetano, C Dupaquier, P Maurel
IEEE Geoscience and Remote Sensing Letters 14 (10), 1685-1689, 2017
303 2017 Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture D Ienco, R Interdonato, R Gaetano, DHT Minh
ISPRS Journal of Photogrammetry and Remote Sensing 158, 11-22, 2019
293 2019 Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatch L Pibre, P Jérôme, D Ienco, M Chaumont
arXiv preprint arXiv:1511.04855, 2015
210 * 2015 DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn R Interdonato, D Ienco, R Gaetano, K Ose
ISPRS journal of photogrammetry and remote sensing 149, 91-104, 2019
167 2019 Deep recurrent neural networks for winter vegetation quality mapping via multitemporal SAR Sentinel-1 DHT Minh, D Ienco, R Gaetano, N Lalande, E Ndikumana, F Osman, ...
IEEE Geoscience and Remote Sensing Letters 15 (3), 464-468, 2018
150 * 2018 Do more views of a graph help? community detection and clustering in multi-graphs EE Papalexakis, L Akoglu, D Ience
Proceedings of the 16th International Conference on Information Fusion, 899-905, 2013
146 2013 From context to distance: Learning dissimilarity for categorical data clustering D Ienco, RG Pensa, R Meo
ACM Transactions on Knowledge Discovery from Data (TKDD) 6 (1), 1-25, 2012
131 2012 P Benedetti, D Ienco, R Gaetano, K Ose, RG Pensa, S Dupuy
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
121 2018 Fuzzy extensions of the DBScan clustering algorithm D Ienco, G Bordogna
Soft Computing 22 (5), 1719-1730, 2018
101 2018 Mapping irrigated areas using Sentinel-1 time series in Catalonia, Spain H Bazzi, N Baghdadi, D Ienco, M El Hajj, M Zribi, H Belhouchette, ...
Remote Sensing 11 (15), 1836, 2019
90 2019 A two-branch CNN architecture for land cover classification of PAN and MS imagery R Gaetano, D Ienco, K Ose, R Cresson
Remote Sensing 10 (11), 1746, 2018
87 * 2018 Clustering based active learning for evolving data streams D Ienco, A Bifet, I Žliobaitė, B Pfahringer
International Conference on Discovery Science, 79-93, 2013
80 2013 The meme ranking problem: Maximizing microblogging virality D Ienco, F Bonchi, C Castillo
2010 IEEE International Conference on Data Mining Workshops, 328-335, 2010
80 2010 Context-based distance learning for categorical data clustering D Ienco, RG Pensa, R Meo
Advances in Intelligent Data Analysis VIII: 8th International Symposium on …, 2009
78 2009 Local community detection in multilayer networks R Interdonato, A Tagarelli, D Ienco, A Sallaberry, P Poncelet
Data Mining and Knowledge Discovery 31, 1444-1479, 2017
71 2017 Unsupervised change detection analysis in satellite image time series using deep learning combined with graph-based approaches E Kalinicheva, D Ienco, J Sublime, M Trocan
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020
64 2020 Parameter-less co-clustering for star-structured heterogeneous data D Ienco, C Robardet, RG Pensa, R Meo
Data Mining and Knowledge Discovery 26, 217-254, 2013
59 2013 A semisupervised approach to the detection and characterization of outliers in categorical data D Ienco, RG Pensa, R Meo
IEEE transactions on neural networks and learning systems 28 (5), 1017-1029, 2016
54 2016 A graph-based approach to detect spatiotemporal dynamics in satellite image time series F Guttler, D Ienco, J Nin, M Teisseire, P Poncelet
ISPRS Journal of Photogrammetry and Remote Sensing 130, 92-107, 2017
53 2017 Exploration and reduction of the feature space by hierarchical clustering D Ienco, R Meo
Proceedings of the 2008 siam international conference on data mining, 577-587, 2008
52 2008 
Raffaele GaetanoCIRAD, UMR TETISAdresse e-mail validée de cirad.fr
