Dino Ienco
Publications
Publications
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When machine learning extrapolates in space: how local data shape spatial transferability2026 |
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Fire severity and recovery across Europe: insights from forest diversity and landscape metrics2025 |
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ProMM-RS : Exploration de l'apprentissage probabiliste pour les représentations multi-modales d'images de télédétectionORASIS 2025 - 20ème Journées francophones des jeunes chercheurs en vision par ordinateur, ISEN Yncréa Ouest, Jun 2025, Le Croisic, France |
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Towards a Multimodal Framework for Remote Sensing Image Change Retrieval and Captioning27. International Conference on Discovery Science, Oct 2024, Pisa, Italy. pp.231-245, ⟨10.1007/978-3-031-78980-9_15⟩ |
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PDiscoFormer: Relaxing Part Discovery Constraints with Vision TransformersECCV 2024 - 18th European Conference on Computer Vision, Sep 2024, Milano, Italy. pp.256-272, ⟨10.1007/978-3-031-73013-9_15⟩ |
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ProMM-RS: Exploring Probabilistic Learning for Multi-Modal Remote Sensing Image Representations2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), Feb 2025, Tucson, United States. pp.517-525, ⟨10.1109/WACVW65960.2025.00063⟩ |
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Revisiting Cross-Modal Knowledge Distillation: A Disentanglement Approach for RGBD Semantic SegmentationEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML_PKDD), Sep 2025, Porto, Portugal |
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SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), Feb 2025, Tucson, United States. pp.13, ⟨10.1109/WACV61041.2025.00552⟩ |
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Transfer Land Cover Maps Across Years: A Time Series-based Semantic Segmentation ApproachJURSE 2025 - Joint Urban Remote Sensing Event, May 2025, Tunis, Tunisia. ⟨10.1109/JURSE60372.2025.11076059⟩ |
Rapeseed Fields Mapping Using Sentinel-1 Time SeriesIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Jul 2024, Athènes, Greece. pp.4836-4840, ⟨10.1109/IGARSS53475.2024.10642836⟩ |
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Joint Cloud Removal and Classification of Sentinel-2 Image Time Series for Agricultural Land Cover Mapping in Northern BeninIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Jul 2024, Athènes, Greece. pp.4824-4827, ⟨10.1109/IGARSS53475.2024.10641427⟩ |
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DisCoM-KD: Cross-Modal Knowledge Distillation via Disentanglement Representation and Adversarial Learning35. British Machine Vision Conference (BMVC 2024), Nov 2024, Glasgow, United Kingdom |
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Potential of Spectral-Spatial Analysis to Map Forest Tree Dieback Due to Bark Beetle Hotspots in Sentinel-2 ImagesIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Jul 2024, Athènes, Greece. pp.5227-5230, ⟨10.1109/IGARSS53475.2024.10641479⟩ |
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Integrating Predictive Process Monitoring Techniques in Smart AgricultureISMIS 2024 - 27. International symposium on methodologies for intelligent systems, Jun 2024, Poitiers, France. pp.306-313, ⟨10.1007/978-3-031-62700-2_27⟩ |
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Semi Supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-LabellingECML PKDD 2024 - European Conference on Machine Learning and Knowledge Discovery in Databases, Sep 2024, Vilnius, Lithuania. pp.440-456, ⟨10.1007/978-3-031-70352-2_26⟩ |
Country-Scale Mapping Of Forest Parameters Using Deep Learning And Tandem-X Insar DataIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Jul 2024, Athènes, Greece. pp.2279-2284, ⟨10.1109/IGARSS53475.2024.10641186⟩ |
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Aligning Geo-Tagged Clip Representations and Satellite Imagery for Few-Shot Land Use ClassificationIGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Jul 2024, Athènes, Greece. pp.319-323, ⟨10.1109/IGARSS53475.2024.10641235⟩ |
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Coarse-to-Fine Concept Bottleneck Models38. Conference on Neural Information Processing Systems, NeurIPS 2024, Dec 2024, Vancouver, Canada. 20 p |
Counterfactual Explanations for Remote Sensing Time Series Data: an Application to Land Cover ClassificationECML PKDD: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Sep 2023, Torino, Italy. p. 20-36, ⟨10.1007/978-3-031-43430-3_2⟩ |
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Encodage 2D de séries temporelles d'imagerie satellitaires pour l'améliorationTAIMA 2023 - 12. Traitement et Analyse de l'Information : Méthodes et Applications, May 2023, Hammamet, Tunisie. 11 p |
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Masking Strategies for Background Bias Removal in Computer Vision ModelsICCV 2023 - International Conference on Computer Vision, Oct 2023, Paris, France. pp.4399-4407, ⟨10.1109/ICCVW60793.2023.00474⟩ |
Modeling the breeding habitat of the Black Grouse from remote sensing data11. IALE World Congress, International Association for Landscape Ecology (IALE), Jul 2023, Nairobi, Kenya |
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PDiscoNet: Semantically consistent part discovery for fine-grained recognitionICCV 2023 - International Conference on Computer Vision, Oct 2023, Paris, France. pp.1866-1876, ⟨10.1109/ICCV51070.2023.00179⟩ |
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Sparse Linear Concept Discovery ModelsICCV 2023 - International Conference on Computer Vision, IEEE, Oct 2023, Paris, France. pp.2759-2763, ⟨10.1109/ICCVW60793.2023.00292⟩ |
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Apprentissage profond multi-sources pour la cartographie des moraines glaciaires - Multi-source Deep Learning for Glacial Moraine MappingORASIS 2023, Laboratoire LIS, UMR 7020, May 2023, Carqueiranne, France |
Dealing with missing modalities at test time for land cover mapping: A case study on multi-source optical data2022 IEEE 21. Mediterranean Electrotechnical Conference (MELECON), Jun 2022, Palermo, France. pp.621-626, ⟨10.1109/MELECON53508.2022.9842865⟩ |
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Combine Histogram Matching and Domain Adaptation to Cope with Temporal Transfer Learning for the Semantic Segmentation of VHR ImagesIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.409-412, ⟨10.1109/IGARSS46834.2022.9883611⟩ |
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Unsupervised Domain Adaptation Methods for Land Cover Mapping with Optical Satellite Image Time SeriesIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.275-278, ⟨10.1109/IGARSS46834.2022.9884094⟩ |
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Estimating Forest Heights and Wood Volume using a Deep Learning Approach from Gedi Waveform DataIGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.7301-7304, ⟨10.1109/IGARSS46834.2022.9883973⟩ |
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Explaining a deep spatiotemporal land cover classifier with attention and redescription mining24. ISPRS Congress (ISPRS 2022), Jun 2022, Nice, France. pp.673-680, ⟨10.5194/isprs-archives-XLIII-B3-2022-673-2022⟩ |
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Classification multi-modale de l'occupation du sol à partir de réseaux de neurones convolutifs et de l'auto-distillationORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France |
A neural network strategy for supervised classification via the Learning Under Privileged Information paradigmSEBD 2021: Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), Sep 2021, Pizzo Calabro, Italy. pp.83-93 |
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CHANNEL-BASED ATTENTION FOR LCC USING SENTINEL-2 TIME SERIESIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Jul 2021, Brussels, Belgium. pp.1077-1080, ⟨10.1109/IGARSS47720.2021.9554205⟩ |
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Adaptation de domaine pour la cartographie de l'occupation des sols à partir de séries temporelles d'images satellitaires optiquesORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France |
Assessment of Urban Land-Cover Classification: Comparison Between Pixel and Object ScalesIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Jul 2021, Brussels, Belgium. pp.5716-5719, ⟨10.1109/IGARSS47720.2021.9554617⟩ |
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An inductive framework for semi-supervised learning29. Italian Symposium on Advanced Database Systems, SEBD 2021, Sep 2021, Pizzo Calabro, Italy. pp.173243 |
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On Enhanced Ensemble Learning for Multimodal Remote Sensing Data Analysis by Capacity OptimizationSSP 2021 - 2021 IEEE Workshop Statistical Signal Processing, Jul 2021, Rio de Janeiro, Brazil. pp.151-155, ⟨10.1109/SSP49050.2021.9513780⟩ |
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A neural network strategy for supervised classification via the learning under privileged information paradigm29. Italian Symposium on Advanced Database Systems, SEBD 2021, Sep 2021, Pizzo Calabro, Italy. pp.173243 |
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Tutorial: Machine and Deep Learning for Earth Observation: Advanced Approaches and Practical Use Cases – AbstractSEBD 2021: Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), Sep 2021, Pizzo Calabro, Italy. pp.iv- iv |
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Evaluate Pseudo Labeling and CNN for Multi-variate Time Series Classification in Low-Data Regimes30th International Conference on Artificial Neural Networks, ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.126-137, ⟨10.1007/978-3-030-86383-8_10⟩ |
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Potential of Sentinel-1 and Sentinel-2 data for mapping irrigated areas at plot scaleEGU General Assenbly 2020, May 2020, Vienna, Austria. ⟨10.5194/egusphere-egu2020-10367⟩ |
Supervised level-wise pretraining for sequential data classificationICONIP 2020 - 27th International Conference on Neural Information Processing, Nov 2020, Bangkok, Thailand. pp.449-457, ⟨10.1007/978-3-030-63823-8_52⟩ |
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Generalized knowledge distillation for multi-sensor remote sensing classification: an application to land cover mappingISPRS Congress 2020 Commission II, ISPRS, Aug 2020, s.l., France. pp.997-1003, ⟨10.5194/isprs-annals-V-2-2020-997-2020⟩ |
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Deep Multivariate Time Series Embedding Clustering via Attentive-Gated AutoencoderPAKDD 2020 - 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, May 2020, Singapore, Singapore. pp.318-329, ⟨10.1007/978-3-030-47426-3_25⟩ |
Irrigation mapping using Sentinel-1 time seriesIGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Sep 2020, Waikoloa, Hawaii, United States. pp.4711-4714, ⟨10.1109/IGARSS39084.2020.9324358⟩ |
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Optical image gap filling using deep convolutional autoencoder from optical and radar imagesIGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Jul 2019, Yokohama, Japan. pp.218-221 |
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Deep triplet-driven semi-supervised embedding clusteringDS 2019 - 22nd International Conference on Discovery Science, Oct 2019, Split, Croatia. pp.220-234, ⟨10.1007/978-3-030-33778-0_18⟩ |
Combining Sentinel-1 and Sentinel-2 time series via RNN for object-based land cover classificationIGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Jul 2019, Yokohama, Japan. pp.4881-4884 |
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Combining Sentinel-1 and Sentinel-2 Time Series via RNN for object-based land cover classificationIGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE; GRSS, Jul 2019, Yokohama, Japan. pp.4881-4884, ⟨10.1109/IGARSS.2019.8898458⟩ |
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How to Deal with Multi-source Data for Tree Detection Based on Deep Learning5th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Nov 2017, Montreal, Canada. pp.1150-1154, ⟨10.1109/GlobalSIP.2017.8309141⟩ |
APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTADevelopments, Technologies and Applications in Remote Sensing / International Society of Photogrammetry and Remote Sensing, May 2018, Beijing, China |
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Multi-annual Satellite Image Time Series Analysis using an Object-Oriented ApproachGEOBIA 2018 - From pixels to ecosystems and global sustainability , Centre d'Etudes Spatiales de la BIOsphère (CESBIO); Office national d'études et de recherches aérospatiales (ONERA); Espace pour le développement (ESPACE DEV); Société T.E.T.I.S, Jun 2018, Montpellier, France |
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Visual Querying of Large Multilayer GraphsSSDBM: Scientific and Statistical Database Management, Jul 2018, Bozen-Bolzano, Italy. pp.32-34, ⟨10.1145/3221269.3223027⟩ |
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Semi-Supervised Clustering With Multiresolution AutoencodersIJCNN: International Joint Conference on Neural Networks, Jul 2018, Rio de Janeiro, Brazil. pp.8, ⟨10.1109/IJCNN.2018.8489353⟩ |
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Node-Centric Community Detection in Multilayer Networks with Layer-Coverage Diversification BiasCompleNet, Mar 2017, Dubrovnik, Croatia. pp.57-66, ⟨10.1007/978-3-319-54241-6_5⟩ |
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Étude des réseaux de neurones sur la stéganalyseCORESA: COmpression et REprésentation des Signaux Audiovisuels, May 2016, Nancy, France |
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RetweetPatterns: Detection of Spatio-Temporal Patterns of Retweets4th World Conference on Information Systems and Technologies (WorldCIST), Mar 2016, Recife, Brazil. pp.879-888, ⟨10.1007/978-3-319-31232-3_83⟩ |
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Querying RDF Data Using A Multigraph-based Approach19. International Conference on Extending Database Technology (EDBT 2016), Mar 2016, Bordeaux, France. pp.245-256, ⟨10.5441/002/edbt.2016.24⟩ |
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Multilayer Graph Edge BundlingIEEE Pacific Visualization Symposium (PacificVis), Apr 2016, Taipei, Taiwan. pp.184-188, ⟨10.1109/PACIFICVIS.2016.7465267⟩ |
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SuMGra: Querying Multigraphs via Efficient IndexingDEXA 2016 - 27th International Conference on Database and Expert Systems Applications, Sep 2016, Porto, Portugal. pp.387-401, ⟨10.1007/978-3-319-44403-1_24⟩ |
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Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatchEI: Electronic Imaging, Feb 2016, San Fransisco, United States |
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Layer-Centered Approach for Multigraphs Visualization19th International Conference Information Visualisation (IV), Jul 2015, Barcelone, Spain. pp.50-55, ⟨10.1109/iv.2015.20⟩ |
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Towards Linked Data Extraction From TweetsEGC: Extraction et Gestion des Connaissances, Jan 2015, Luxembourg, Luxembourg. pp.383-388 |
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Mining Multi-Relational Gradual PatternsSDM 2015 - 15th SIAM International Conference on Data Mining, Apr 2015, Vancouver, Canada. pp.846-854, ⟨10.1137/1.9781611974010.95⟩ |
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Knowledge-Based Representation for Transductive Multilingual Document Classification37. European Conference on Information Retrieval (ECIR), Mar 2015, Vienna, Austria. pp.92-103, ⟨10.1007/978-3-319-16354-3_11⟩ |
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Multilingual document classification via transductive learning6th Italian Information Retrieval Workshop, May 2015, Cagliari, Italy. 4 p |
Fuzzy core DBScan clustering algorithmIPMU, Jul 2014, Montpellier, France |
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Exploring high repetitivity remote sensing time series for mapping and monitoring natural habitats — A new approach combining OBIA and k-partite graphsIEEE International Symposium on Geoscience and Remote Sensing (IGARSS), Jul 2014, Quebec City, Canada. pp.3930-3933, ⟨10.1109/IGARSS.2014.6947344⟩ |
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Change detection in categorical evolving data streamsSAC 2014 - 29th Annual ACM Symposium on Applied Computing, Mar 2014, Gyeongju, South Korea. pp.792-797, ⟨10.1145/2554850.2554864⟩ |
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Monitoring the phenology of mediterranean natural habitats with multispectral sensors: an analysis based on multiseasonal field spectraInternational Geoscience and Remote Sensing Symposium (IGARSS), 35th Canadian Symposium on Remote Sensing, CSRS 2014, Jul 2014, Québec, Canada. pp.3934-3937, ⟨10.1109/IGARSS.2014.6947345⟩ |
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Détection de changements dans des flots de données qualitatives14e Journées Internationales Francophones sur l'Extraction et la Gestion des Connaissances (EGC), Jan 2014, Rennes, France. pp.517-520 |
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Contextual Itemset Mining in DBpediaLD4KD: Linked Data for Knowledge Discovery, Sep 2014, Nancy, France. pp.27-36 |
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Semantic-based multilingual document clustering via tensor modelingEMNLP, Conference on Empirical Methods in Natural Language Processing, Oct 2014, Doha, France. 10 p |
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Towards the use of sequential patterns for detection and characterization of natural and agricultural areas15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Jul 2014, Montpellier, France. pp.97-106, ⟨10.1007/978-3-319-08795-5_11⟩ |
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Semantic-Based Multilingual Document Clustering via Tensor ModelingEMNLP: Empirical Methods in Natural Language Processing, Oct 2014, Doha, Qatar. pp.600-609, ⟨10.3115/v1/D14-1065⟩ |
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Identifying cropped areas in small growers agricultural regions using data mining for food securitySentinel-2 for Science Workshop at ESA-ESRIN, May 2014, Frascati, Italy |
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High density-focused uncertainty sampling for active learning over evolving stream dataBigMine 2014, Aug 2014, New York, United States. pp.133-148 |
Do more views of a graph help? Community detection and clustering in multi-GraphsFUSION 2013, Jul 2013, Istanbul, Turkey. pp.899-905 |
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How to Extract Relevant Knowledge from Tweets?International Workshop on Information Search, Integration, and Personalization (ISIP), Oct 2012, Sapporo, Japan. pp.111-120, ⟨10.1007/978-3-642-40140-4_12⟩ |
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Clustering based active learning for evolving data streamsDiscovery Science, Oct 2013, Singapore, Singapore. pp.15, ⟨10.1007/978-3-642-40897-7_6⟩ |
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Healtcare Trajectory Mining by Combining Multi-dimensional Component and ItemsetsNFMCP: New Frontiers in Mining Complex Patterns, Sep 2012, Bristol, United Kingdom. ⟨10.1007/978-3-642-37382-4_8⟩ |
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Mining Representative Movement Patterns through CompressionPAKDD 2013 - 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Apr 2013, Gold Coast, Australia. pp.314-326, ⟨10.1007/978-3-642-37453-1_26⟩ |
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Knowledge-free table summarization15th International Conference, DaWaK 2013, Aug 2013, Prague, Czech Republic. pp.122-133, ⟨10.1007/978-3-642-40131-2_11⟩ |
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Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Patten Mining SystemECML PKDD 2012 - Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Sep 2012, Bristol, United Kingdom. pp.820-823, ⟨10.1007/978-3-642-33486-3_55⟩ |
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French Presidential Elections: What are the most Efficient Measures for Tweets?PLEAD: Proceedings of the Workshop Politics, Elections and Data, 2012, Maui, United States. pp.23-30, ⟨10.1145/2389661.2389669⟩ |
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Mining Time Relaxed Gradual Moving Object Clusters20th ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Nov 2012, Redondo Beach, United States. pp.478-481, ⟨10.1145/2424321.2424394⟩ |
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Towards an Automatic Construction of Contextual Attribute-Value Taxonomies27th International Symposium on Applied Computing (SAC), Mar 2012, Riva del Garda, Trento, Italy. pp.113-118, ⟨10.1145/2245276.2245301⟩ |
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Healthcare trajectory mining by combining multidimensional component and itemsetsECML-PKDD 2012, Sep 2012, Bristol, United Kingdom. p. 116 - p. 127 |
Toward Geographic Information Harvesting: Extraction of Spatial Relational Facts from Web Documents12th International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM) @ ICDM, Dec 2012, Brussels, Belgium. pp.789-796, ⟨10.1109/ICDMW.2012.20⟩ |
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Mining Fuzzy Moving Object ClustersADMA 2012 - 8th International Conference on Advanced Data Mining and Applications, Dec 2012, Nanjing, China. pp.100-114, ⟨10.1007/978-3-642-35527-1_9⟩ |
An Unsupervised Framework for Topological Relations Extraction from Geographic DocumentsDEXA 2012 - 23rd International Conference on Database and Expert Systems Applications, 2012, Vienna, Austria. pp.48-55, ⟨10.1007/978-3-642-32597-7_5⟩ |
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Vers une méthode automatique de construction de hiérarchies contextuellesEGC: Extraction et Gestion des Connaissances, 2012, Bordeaux, France. pp.335-346 |
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Comprehensive regional assessment of brood habitat suitability for Alpine black grouse (Lyrurus tetrix)BIOSPACE25 - BIODIVERISTY INSIGHT FROM SPACE, Feb 2025, Frascati, Italy |
A dual viewpoint deep learning architecture for time series classification2019 Living Planet Symposium (LPS 2019), May 2019, Milan, Italy. ESA [European Space Agency], 1 p., 2019 |
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Visual Querying and Exploring of Large Multilayer GraphsVIS, Oct 2018, Berlin, Germany. IEEE, Conference on Scientific Visualization, Information Visualization and Visual Analytics, 2018 |
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Results of IndexMed GRAIL Days 2016: How to use standards to build GRAphs and mIne data for environmentaL research? IndexMeed consortium for data mining in ecologyRDA Ninth Plenary Meeting "Data Infrastructures for Open Science", Apr 2017, Barcelona, Spain. , 2017, ⟨10.13140/RG.2.2.32504.44806⟩ |
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Local community detection in multilayer networksASONAM, Aug 2016, San Francisco, United States. IEEE/ACM, pp.1382-1383, 2016 |
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Twitter Event Detection and Modeling with TEWSISWC: International Semantic Web Conference, Oct 2015, Bethlehem, PA, United States. , 14th International Semantic Web Conference, pp.4, 2015, Posters & Demonstrations Track |
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Modeling black grouse brood habitat in the French Alps using remote sensing2024, 26 p |
Discovery Science - 25th International Conference, DS 2022, Montpellier, France, October 10-12, 2022, ProceedingsDS 2022 - 25th International Conference on Discovery Science, Oct 2022, Montpellier, France. Lecture Notes in Computer Science, 13601, Springer Nature Switzerland, 2022, Lecture Notes in Computer Science, 978-3-031-18840-4. ⟨10.1007/978-3-031-18840-4⟩ |
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Towards combining satellite imagery and VGI for urban LULC classification2019 Joint Urban Remote Sensing Event (JURSE), Apr 2019, Vannes, France. Institute of Electrical and Electronics Engineers Inc., pp.1-4, 2019, ⟨10.1109/JURSE.2019.8808966⟩ |
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IndexMEED cases studies using "Omics" data with graph theoryTDWG, 2017, Ottawa, Canada. Biodiversity Information Science and Standards, 1, pp.340-361, 2017, ⟨10.3897/tdwgproceedings.1.20740⟩ |
Proceedings of the First Workshop on Modeling, Learning and Mining for Cross/Multilinguality (MultiLingMine 2016) co-located with the 38th European Conference on Information Retrieval (ECIR 2016), Padova, Italy, March 20, 2016.MultiLingMine: Modeling, Learning and Mining for Cross/Multilinguality, Mar 2016, Padova, Italy. 1589, , 2016, CEUR Workshop Proceedings |
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Fondements et état de l'artBellon-Maurel Véronique (ed.); Brossard Ludovic (ed.); Garcia Frédérick (ed.); Mitton Nathalie (ed.); Terrier Alexandre (ed.). Agriculture et numérique : un Livre Blanc d’Inria et INRAE pour construire les bases d’une agriculture numérique responsable, 6, INRIA; INRAE, pp.32-82, 2022, Livre blanc / INRIA |
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Foundations and state of playAgriculture and Digital Technology: Getting the most out of digital technology to contribute to the transition to sustainable agriculture and food systems, 6, INRIA, pp.30-75, 2022, White book Inrira, 978-2-7261-1310-3 |
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Querying RDF Data: A Multigraph Based ApproachOlivier Pivert. NoSQL Data Models • Trends and Challenges, 1, ISTE–WILEY, 2018, Base de données et Big Data • Databases and Big Data, 9781786303646. ⟨10.1002/9781119528227.ch5⟩ |
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Mining and learning from spatio-temporal data: examples and perspectivesEnvironmental Sciences. HDR en Informatique, Université de Montpellier, 2016 |
Process for identifying rare eventsUnited States, Patent n° : EP13153512A; EP2014051963W. 2013 |