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 | 288 | 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 | 268 | 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 | 206* | 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 | 151 | 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 | 146* | 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 | 145 | 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 | 127 | 2012 |
: A Deep Learning Architecture for Multiscale Multimodal Multitemporal Satellite Data Fusion P Benedetti, D Ienco, R Gaetano, K Ose, RG Pensa, S Dupuy IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 117 | 2018 |
Fuzzy extensions of the DBScan clustering algorithm D Ienco, G Bordogna Soft Computing 22 (5), 1719-1730, 2018 | 96 | 2018 |
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 | 82* | 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 | 81 | 2019 |
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 |
Clustering based active learning for evolving data streams D Ienco, A Bifet, I Žliobaitė, B Pfahringer International Conference on Discovery Science, 79-93, 2013 | 77 | 2013 |
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 | 76 | 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 | 66 | 2017 |
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 | 58 | 2013 |
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 | 57 | 2020 |
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 | 51 | 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 | 49 | 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 | 49 | 2008 |