Dino Ienco

159
Documents

Publications

Publications

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Comprehensive regional assessment of brood habitat suitability for Alpine black grouse (Lyrurus tetrix)

Samuel Alleaume , Alexandre Tm Defossez , Marc Montadert , Dino Ienco , Nadia Guiffant et al.
BIOSPACE25 - BIODIVERISTY INSIGHT FROM SPACE, Feb 2025, FRASCATI, Italy
Poster de conférence hal-04929144 v1
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Visual Querying and Exploring of Large Multilayer Graphs

Erick Cuenca Pauta , Arnaud Sallaberry , Dino Ienco , Pascal Poncelet
VIS, Oct 2018, Berlin, Germany. IEEE, Conference on Scientific Visualization, Information Visualization and Visual Analytics, 2018
Poster de conférence lirmm-01912384 v1
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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 ecology

Romain David , Jean-Pierre Féral , Anne-Sophie Archambeau , Fanny Arnaud , David Auber et al.
RDA Ninth Plenary Meeting "Data Infrastructures for Open Science", Apr 2017, Barcelona, Spain. , 2017, ⟨10.13140/RG.2.2.32504.44806⟩
Poster de conférence hal-02295974 v1
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Local community detection in multilayer networks

Roberto Interdonato , Andrea Tagarelli , Dino Ienco , Arnaud Sallaberry , Pascal Poncelet
ASONAM, Aug 2016, San Francisco, United States. IEEE/ACM, pp.1382-1383, 2016
Poster de conférence hal-02605181 v1
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Twitter Event Detection and Modeling with TEWS

Mykael Vigo , Zohra Bellahsene , Dino Ienco , Konstantin Todorov
ISWC: International Semantic Web Conference, Oct 2015, Bethlehem, PA, United States. , 14th International Semantic Web Conference, pp.4, 2015, Posters & Demonstrations Track
Poster de conférence lirmm-01239194 v1
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SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting

Pallavi Jain , Dino Ienco , Roberto Interdonato , Tristan Berchoux , Diego Marcos
IEEE/CVF Winter Conference on Applications of Computer Vision - WACV 2025, Feb 2025, Tucson (AZ), United States
Communication dans un congrès hal-04971161 v1
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PDiscoFormer: Relaxing Part Discovery Constraints with Vision Transformers

Ananthu Aniraj , Cassio F. Dantas , Dino Ienco , Diego Marcos
ECCV 2024 - 18th European Conference on Computer Vision, Sep 2024, Milano, Italy. pp.256-272, ⟨10.1007/978-3-031-73013-9_15⟩
Communication dans un congrès hal-04659631 v1
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Towards a Multimodal Framework for Remote Sensing Image Change Retrieval and Captioning

Roger Ferrod , Luigi Di Caro , Dino Ienco
27th International Conference on Discovery Science, Oct 2024, Pisa, Italy. pp.231-245, ⟨10.1007/978-3-031-78980-9_15⟩
Communication dans un congrès hal-05050679 v1
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DisCoM-KD: Cross-Modal Knowledge Distillation via Disentanglement Representation and Adversarial Learning

Dino Ienco , Cassio Fraga Dantas
BMVC 2024 - 35th British Machine Vision Conference, Nov 2024, Glasgow, United Kingdom
Communication dans un congrès hal-04666307 v1
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Integrating Predictive Process Monitoring Techniques in Smart Agriculture

Simona Fioretto , Dino Ienco , Roberto Interdonato , Elio Masciari
ISMIS 2024 - 27. International symposium on methodologies for intelligent systems, Jun 2024, Poitiers, France. pp.306-313, ⟨10.1007/978-3-031-62700-2_27⟩
Communication dans un congrès hal-04619543 v1
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Semi Supervised Heterogeneous Domain Adaptation via Disentanglement and Pseudo-Labelling

Cassio F. Dantas , Raffaele Gaetano , Dino Ienco
ECML 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⟩
Communication dans un congrès hal-04617917 v1
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Coarse-to-Fine Concept Bottleneck Models

Konstantinos Panousis , Dino Ienco , Diego Marcos
NeurIPS 2024 - 38th Annual Conference on Neural Information Processing Systems, Dec 2024, Vancouver, Canada
Communication dans un congrès hal-04709806 v1
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Masking Strategies for Background Bias Removal in Computer Vision Models

Ananthu Aniraj , Cassio F. Dantas , Dino Ienco , Diego Marcos
Out of Distribution Generalization in Computer Vision workshop (in conjunction with ICCV 2023), Oct 2023, Paris, France. pp.4399-4407, ⟨10.1109/ICCVW60793.2023.00474⟩
Communication dans un congrès hal-04184449 v1
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Encodage 2D de séries temporelles d'imagerie satellitaires pour l'amélioration

Azza Abidi , Dino Ienco , A. Ben Abbes , Imed Riadh Farah
TAIMA 2023 - 12e Traitement et Analyse de l'Information : Méthodes et Applications, May 2023, Hammamet, Tunisie
Communication dans un congrès hal-04689663 v1
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PDiscoNet: Semantically consistent part discovery for fine-grained recognition

Robert van der Klis , Stephan Alaniz , Massimiliano Mancini , Cassio F. Dantas , Dino Ienco et al.
ICCV 2023 - International Conference on Computer Vision, Oct 2023, Paris, France. pp.1866-1876, ⟨10.1109/ICCV51070.2023.00179⟩
Communication dans un congrès hal-04183747 v1

Sparse Linear Concept Discovery Models

Konstantinos Panousis , Dino Ienco , Diego Marcos
ICCVW 2023 - IEEE/CVF International Conference on Computer Vision Workshops, IEEE, Oct 2023, Paris, France. pp.2759-2763, ⟨10.1109/ICCVW60793.2023.00292⟩
Communication dans un congrès hal-04532065 v1

Counterfactual Explanations for Remote Sensing Time Series Data: an Application to Land Cover Classification

Cassio F. Dantas , Thalita F Drumond , Diego Marcos , Dino Ienco
ECML 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⟩
Communication dans un congrès hal-04189631 v1

Dealing with missing modalities at test time for land cover mapping: A case study on multi-source optical data

Yawogan Jean Eudes Gbodjo , Dino Ienco
2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), Jun 2022, Palermo, France. pp.621-626, ⟨10.1109/MELECON53508.2022.9842865⟩
Communication dans un congrès hal-03760307 v1

Estimating Forest Heights and Wood Volume using a Deep Learning Approach from Gedi Waveform Data

Ibrahim Fayad , Dino Ienco , Nicolas Baghdadi , Raffaele Gaetano , Clayton Alcarde Alvares et al.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 2022, Kuala Lumpur, Malaysia. pp.7301-7304, ⟨10.1109/IGARSS46834.2022.9883973⟩
Communication dans un congrès hal-03837968 v1
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Explaining a deep spatiotemporal land cover classifier with attention and redescription mining

N. Méger , H. Courteille , A Benoit , A. Atto , Dino Ienco
The XXIV International Society for Photogrammetry and Remote Sensing Congress, Jun 2022, Nice, France. pp.673-680, ⟨10.5194/isprs-archives-XLIII-B3-2022-673-2022⟩
Communication dans un congrès hal-03694444 v1
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Classification multi-modale de l'occupation du sol à partir de réseaux de neurones convolutifs et de l'auto-distillation

Yawogan Jean Eudes Gbodjo , Dino Ienco
ORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France
Communication dans un congrès hal-03339628 v1
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CHANNEL-BASED ATTENTION FOR LCC USING SENTINEL-2 TIME SERIES

Hermann Courteille , A Benoit , N Méger , A Atto , Dino Ienco
International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Jul 2021, Brussels, Belgium. pp.1077-1080, ⟨10.1109/IGARSS47720.2021.9554205⟩
Communication dans un congrès hal-03182049 v1

An inductive framework for semi-supervised learning

Shuyi Yang , Dino Ienco , R. Esposito , R.G. Pensa
29th Italian Symposium on Advanced Database Systems, SEBD 2021, Sep 2021, Pizzo Calabro, Italy. pp.173243
Communication dans un congrès hal-03444184 v1
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Adaptation de domaine pour la cartographie de l'occupation des sols à partir de séries temporelles d'images satellitaires optiques

Emmanuel Capliez , Dino Ienco , Raffaele Gaetano , Nicolas Baghdadi , Adrien Hadj Salah
ORASIS 2021, Centre National de la Recherche Scientifique [CNRS], Sep 2021, Saint Ferréol, France
Communication dans un congrès hal-03339618 v1

On Enhanced Ensemble Learning for Multimodal Remote Sensing Data Analysis by Capacity Optimization

Saloua Chlaily , Dino Ienco , Christian Jutten , Andrea Marinoni
SSP 2021 - 2021 IEEE Workshop Statistical Signal Processing, Jul 2021, Rio de Janeiro, Brazil. pp.151-155, ⟨10.1109/SSP49050.2021.9513780⟩
Communication dans un congrès hal-03597523 v1

A neural network strategy for supervised classification via the learning under privileged information paradigm

L. Sacco , Dino Ienco , Roberto Interdonato
29th Italian Symposium on Advanced Database Systems, SEBD 2021, Sep 2021, Pizzo Calabro, Italy. pp.173243
Communication dans un congrès hal-03444517 v1

Evaluate Pseudo Labeling and CNN for Multi-variate Time Series Classification in Low-Data Regimes

Dino Ienco , Davi Pereira-Santos , André de Carvalho
30th International Conference on Artificial Neural Networks, ICANN 2021, Sep 2021, Bratislava, Slovakia. pp.126-137, ⟨10.1007/978-3-030-86383-8_10⟩
Communication dans un congrès hal-03375996 v1
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Potential of Sentinel-1 and Sentinel-2 data for mapping irrigated areas at plot scale

Hassan Bazzi , Nicolas Baghdadi , Dino Ienco , Mehrez Zribi , Hatem Belhouchette
EGU General Assenbly 2020, May 2020, Vienna, Austria. ⟨10.5194/egusphere-egu2020-10367⟩
Communication dans un congrès hal-02881880 v1

Supervised level-wise pretraining for sequential data classification

Dino Ienco , Roberto Interdonato , Raffaele Gaetano
ICONIP 2020 - 27th International Conference on Neural Information Processing, Nov 2020, Bangkok, Thailand. pp.449-457, ⟨10.1007/978-3-030-63823-8_52⟩
Communication dans un congrès hal-03031531 v1

Irrigation mapping using Sentinel-1 time series

Hassan Bazzi , Nicolas Baghdadi , Dino Ienco , Mehrez Zribi , Hatem Belhouchette
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Sep 2020, Waikoloa, Hawaii, United States. pp.4711-4714, ⟨10.1109/IGARSS39084.2020.9324358⟩
Communication dans un congrès hal-03322931 v1
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Deep Multivariate Time Series Embedding Clustering via Attentive-Gated Autoencoder

Dino Ienco , Roberto Interdonato
PAKDD 2020 - 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, May 2020, Singapour, Singapore. pp.318-329, ⟨10.1007/978-3-030-47426-3_25⟩
Communication dans un congrès hal-02923636 v1

Optical image gap filling using deep convolutional autoencoder from optical and radar images

Rémi Cresson , Dino Ienco , R. Gaetano , Kenji Ose , Dinh Ho Tong Minh
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2019, Yokohama, Japan. pp.218-221
Communication dans un congrès hal-02968847 v1
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Deep triplet-driven semi-supervised embedding clustering

Dino Ienco , Ruggero Pensa
DS 2019 - 22nd International Conference on Discovery Science, Oct 2019, Split, Croatia. pp.220-234, ⟨10.1007/978-3-030-33778-0_18⟩
Communication dans un congrès hal-02931058 v1

Combining Sentinel-1 and Sentinel-2 time series via RNN for object-based land cover classification

Dino Ienco , Raffaele Gaetano , Kenji Ose , Dinh Ho Tong Minh
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2019, Yokohama, Japan. pp.4881-4884
Communication dans un congrès hal-02966810 v1
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How to Deal with Multi-source Data for Tree Detection Based on Deep Learning

Lionel Pibre , Marc Chaumont , Gérard Subsol , Dino Ienco , Mustapha Derras
5th IEEE Global Conference on Signal and Information Processing (GlobalSIP), Nov 2017, Montreal, Canada. pp.1150-1154, ⟨10.1109/GlobalSIP.2017.8309141⟩
Communication dans un congrès lirmm-01685327 v1

APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTA

Simona Niculescu , Dino Ienco , Jenica Hanganu
Developments, Technologies and Applications in Remote Sensing / International Society of Photogrammetry and Remote Sensing, May 2018, Beijing, China
Communication dans un congrès hal-01804954 v1

Multi-annual Satellite Image Time Series Analysis using an Object-Oriented Approach

Lynda Khiali , Dino Ienco , Maguelonne Teisseire , Samuel Alleaume , Mamadou Ndiath
GEOBIA 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
Communication dans un congrès hal-01958952 v1
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Visual Querying of Large Multilayer Graphs

Erick Cuenca Pauta , Arnaud Sallaberry , Dino Ienco , Pascal Poncelet
SSDBM: Scientific and Statistical Database Management, Jul 2018, Bozen-Bolzano, Italy. pp.32-34, ⟨10.1145/3221269.3223027⟩
Communication dans un congrès lirmm-01847422 v1
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Semi-Supervised Clustering With Multiresolution Autoencoders

Dino Ienco , Ruggero G. Pensa
IJCNN: International Joint Conference on Neural Networks, Jul 2018, Rio de Janeiro, Brazil. pp.8, ⟨10.1109/IJCNN.2018.8489353⟩
Communication dans un congrès hal-01931471 v1
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Node-Centric Community Detection in Multilayer Networks with Layer-Coverage Diversification Bias

Roberto Interdonato , Andrea Tagarelli , Dino Ienco , Arnaud Sallaberry , Pascal Poncelet
CompleNet, Mar 2017, Dubrovnik, Croatia. pp.57-66, ⟨10.1007/978-3-319-54241-6_5⟩
Communication dans un congrès lirmm-01912004 v1
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Multilayer Graph Edge Bundling

Romain Bourqui , Dino Ienco , Arnaud Sallaberry , Pascal Poncelet
IEEE Pacific Visualization Symposium (PacificVis), Apr 2016, Taipei, Taiwan. pp.184-188, ⟨10.1109/PACIFICVIS.2016.7465267⟩
Communication dans un congrès lirmm-01304602 v1
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Querying RDF Data Using A Multigraph-based Approach

Vijay Ingalalli , Dino Ienco , Pascal Poncelet , Serena Villata
EDBT 2016 - 19th International Conference on Extending Database Technology, Mar 2016, Bordeaux, France. pp.245-256, ⟨10.5441/002/edbt.2016.24⟩
Communication dans un congrès lirmm-01245146 v1
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RetweetPatterns: Detection of Spatio-Temporal Patterns of Retweets

Tomy Rodrigues , Tiago Cunha , Dino Ienco , Pascal Poncelet , Carlos Soares
4th World Conference on Information Systems and Technologies (WorldCIST), Mar 2016, Recife, Brazil. pp.879-888, ⟨10.1007/978-3-319-31232-3_83⟩
Communication dans un congrès lirmm-01362428 v1
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SuMGra: Querying Multigraphs via Efficient Indexing

Vijay Ingalalli , Dino Ienco , Pascal Poncelet
DEXA 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⟩
Communication dans un congrès lirmm-01362431 v1
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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-mismatch

Lionel Pibre , Jérôme Pasquet , Dino Ienco , Marc Chaumont
EI: Electronic Imaging, Feb 2016, San Fransisco, United States
Communication dans un congrès lirmm-01227950 v2
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Étude des réseaux de neurones sur la stéganalyse

Lionel Pibre , Marc Chaumont , Dino Ienco , Jérôme Pasquet
CORESA: COmpression et REprésentation des Signaux Audiovisuels, May 2016, Nancy, France
Communication dans un congrès hal-01374095 v1
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Mining Multi-Relational Gradual Patterns

Nhat Hai Phan , Dino Ienco , Donato Malerba , Pascal Poncelet , Maguelonne Teisseire
SDM 2015 - 15th SIAM International Conference on Data Mining, Apr 2015, Vancouver, Canada. pp.846-854, ⟨10.1137/1.9781611974010.95⟩
Communication dans un congrès lirmm-01239187 v1
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Layer-Centered Approach for Multigraphs Visualization

Denis Redondo , Arnaud Sallaberry , Dino Ienco , Faraz Zaidi , Pascal Poncelet
19th International Conference Information Visualisation (IV), Jul 2015, Barcelone, Spain. pp.50-55, ⟨10.1109/iv.2015.20⟩
Communication dans un congrès lirmm-01275379 v1
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Towards Linked Data Extraction From Tweets

Manel Achichi , Zohra Bellahsene , Dino Ienco , Konstantin Todorov
EGC: Extraction et Gestion des Connaissances, Jan 2015, Luxembourg, Luxembourg. pp.383-388
Communication dans un congrès hal-01411403 v1
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Knowledge-Based Representation for Transductive Multilingual Document Classification

Salvatore Romeo , Dino Ienco , Andrea Tagarelli
37th European Conference on Information Retrieval (ECIR), Mar 2015, Vienna, Austria. pp.92-103, ⟨10.1007/978-3-319-16354-3_11⟩
Communication dans un congrès lirmm-01239095 v1
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Multilingual document classification via transductive learning

S. Romeo , Dino Ienco , A. Tagarelli
6th Italian Information Retrieval Workshop, May 2015, Cagliari, Italy. 4 p
Communication dans un congrès hal-01295784 v1
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Monitoring the phenology of mediterranean natural habitats with multispectral sensors: an analysis based on multiseasonal field spectra

C. Corbane , F. Guttler , Samuel Alleaume , Dino Ienco , Maguelonne Teisseire
International 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⟩
Communication dans un congrès hal-01136524 v1
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Semantic-based multilingual document clustering via tensor modeling

S. Romeo , A. Tagarelli , Dino Ienco
EMNLP, Conference on Empirical Methods in Natural Language Processing, Oct 2014, Doha, France. 10 p
Communication dans un congrès hal-01130094 v1
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Contextual Itemset Mining in DBpedia

Julien Rabatel , Madalina Croitoru , Dino Ienco , Pascal Poncelet
LD4KD: Linked Data for Knowledge Discovery, Sep 2014, Nancy, France. pp.27-36
Communication dans un congrès lirmm-01076887 v1
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Détection de changements dans des flots de données qualitatives

Dino Ienco , Albert Bifet , Bernhard Pfahringer , Pascal Poncelet
14e Journées Internationales Francophones sur l'Extraction et la Gestion des Connaissances (EGC), Jan 2014, Rennes, France. pp.517-520
Communication dans un congrès hal-01556565 v1
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Semantic-Based Multilingual Document Clustering via Tensor Modeling

Salvatore Romeo , Andrea Tagarelli , Dino Ienco
EMNLP: Empirical Methods in Natural Language Processing, Oct 2014, Doha, Qatar. pp.600-609, ⟨10.3115/v1/D14-1065⟩
Communication dans un congrès lirmm-01239231 v1
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Identifying cropped areas in small growers agricultural regions using data mining for food security

Elodie Vintrou , Valentine Lebourgeois , Agnès Bégué , Dino Ienco , Maguelonne Teisseire et al.
Sentinel-2 for Science Workshop at ESA-ESRIN, May 2014, Frascati, Italy
Communication dans un congrès hal-02600872 v1
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Towards the use of sequential patterns for detection and characterization of natural and agricultural areas

Fabio N. Güttler , Dino Ienco , Maguelonne Teisseire , Jordi Nin , Pascal Poncelet
15th 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⟩
Communication dans un congrès hal-02600411 v1
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High density-focused uncertainty sampling for active learning over evolving stream data

Dino Ienco , Bernhard Pfahringer , Indrė Žliobaitė
BigMine 2014, Aug 2014, New York, United States. pp.133-148
Communication dans un congrès hal-02600408 v1

Fuzzy core DBScan clustering algorithm

G. Bordogna , Dino Ienco
IPMU, Jul 2014, Montpellier, France
Communication dans un congrès hal-02600410 v1
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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 graphs

Fabio N. Güttler , Samuel Alleaume , Christina Corbane , Dino Ienco , J. Nin et al.
IEEE International Symposium on Geoscience and Remote Sensing (IGARSS), Jul 2014, Quebec City, Canada. pp.3930-3933, ⟨10.1109/IGARSS.2014.6947344⟩
Communication dans un congrès hal-02108532 v1
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Change detection in categorical evolving data streams

Dino Ienco , Albert Bifet , Bernhard Pfahringer , Pascal Poncelet
SAC 2014 - 29th Annual ACM Symposium on Applied Computing, Mar 2014, Gyeongju, South Korea. pp.792-797, ⟨10.1145/2554850.2554864⟩
Communication dans un congrès hal-02600407 v1
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Healtcare Trajectory Mining by Combining Multi-dimensional Component and Itemsets

Elias Egho , Dino Ienco , Nicolas Jay , Amedeo Napoli , Pascal Poncelet et al.
NFMCP: New Frontiers in Mining Complex Patterns, Sep 2012, Bristol, United Kingdom. ⟨10.1007/978-3-642-37382-4_8⟩
Communication dans un congrès lirmm-00732661 v1
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Mining Representative Movement Patterns through Compression

Nhat Hai Phan , Dino Ienco , Pascal Poncelet , Maguelonne Teisseire
PAKDD 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⟩
Communication dans un congrès lirmm-00798072 v1
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How to Extract Relevant Knowledge from Tweets?

Flavien Bouillot , Nhat Hai Phan , Nicolas Béchet , Sandra Bringay , Dino Ienco et al.
International Workshop on Information Search, Integration, and Personalization (ISIP), Oct 2012, Sapporo, Japan. pp.111-120, ⟨10.1007/978-3-642-40140-4_12⟩
Communication dans un congrès lirmm-00798662 v1

Clustering based active learning for evolving data streams

Dino Ienco , Albert Bifet , I. Zliobaite , B. Pfahringer
Discovery Science, Oct 2013, Singapour, Singapore. pp.15, ⟨10.1007/978-3-642-40897-7_6⟩
Communication dans un congrès hal-02599586 v1
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Knowledge-free table summarization

Dino Ienco , Yoann Pitarch , Pascal Poncelet , Maguelonne Teisseire
15th International Conference, DaWaK 2013, Aug 2013, Prague, Czech Republic. pp.122-133, ⟨10.1007/978-3-642-40131-2_11⟩
Communication dans un congrès hal-02599585 v1

Do more views of a graph help? Community detection and clustering in multi-Graphs

E.E. Papalexakis , L. Akoglu , Dino Ienco
FUSION 2013, Jul 2013, Istanbul, Turkey. pp.899-905
Communication dans un congrès hal-02598527 v1
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Mining Time Relaxed Gradual Moving Object Clusters

Nhat Hai Phan , Dino Ienco , Pascal Poncelet , Maguelonne Teisseire
20th ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL), Nov 2012, Redondo Beach, United States. pp.478-481, ⟨10.1145/2424321.2424394⟩
Communication dans un congrès lirmm-00798076 v1
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Extracting Trajectories through an Efficient and Unifying Spatio-Temporal Patten Mining System

Nhat Hai Phan , Dino Ienco , Pascal Poncelet , Maguelonne Teisseire
ECML 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⟩
Communication dans un congrès lirmm-00732662 v1
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French Presidential Elections: What are the most Efficient Measures for Tweets?

Flavien Bouillot , Pascal Poncelet , Mathieu Roche , Dino Ienco , Elnaz Bigdeli et al.
PLEAD: Proceedings of the Workshop Politics, Elections and Data, 2012, Maui, United States. pp.23-30, ⟨10.1145/2389661.2389669⟩
Communication dans un congrès lirmm-00801028 v1
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Towards an Automatic Construction of Contextual Attribute-Value Taxonomies

Dino Ienco , Yoann Pitarch , Pascal Poncelet , Maguelonne Teisseire
27th International Symposium on Applied Computing (SAC), Mar 2012, Riva del Garda, Trento, Italy. pp.113-118, ⟨10.1145/2245276.2245301⟩
Communication dans un congrès lirmm-00798075 v1
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Healthcare trajectory mining by combining multidimensional component and itemsets

Elias Egho , Chedy Raïssi , Dino Ienco , Nicolas Jay , Amedeo Napoli et al.
ECML-PKDD 2012, Sep 2012, Bristol, United Kingdom. p. 116 - p. 127
Communication dans un congrès hal-00801813 v1

Toward Geographic Information Harvesting: Extraction of Spatial Relational Facts from Web Documents

Corrado Loglisci , Dino Ienco , Mathieu Roche , Maguelonne Teisseire , Donato Malerba
12th International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM) @ ICDM, Dec 2012, Brussels, Belgium. pp.789-796, ⟨10.1109/ICDMW.2012.20⟩
Communication dans un congrès lirmm-00816292 v1
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Mining Fuzzy Moving Object Clusters

Nhat Hai Phan , Dino Ienco , Pascal Poncelet , Maguelonne Teisseire
ADMA 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⟩
Communication dans un congrès lirmm-00798148 v1

Vers une méthode automatique de construction de hiérarchies contextuelles

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An Unsupervised Framework for Topological Relations Extraction from Geographic Documents

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DEXA 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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Environmental and bioclimatic data for epidemiological analysis over French Mediterranean areas

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Environmental Data Science, 2025, 3, pp.e31. ⟨10.1017/eds.2024.50⟩
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MARA : a deep learning based framework for multilayer graph simplification

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Neurocomputing, 2025, 612, pp.128712. ⟨10.1016/j.neucom.2024.128712⟩
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Sentinel-1 (S1) time series alignment method for rapeseed fields mapping

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Frontiers in Remote Sensing, 2025, 5, pp.1483295. ⟨10.3389/frsen.2024.1483295⟩
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Multi-sensor Model for Earth Observation Robust to Missing Data via Sensor Dropout and Mutual Distillation

Francisco Mena , Dino Ienco , Cássio Dantas , Roberto Interdonato , Andreas Dengel
IEEE Access, In press, ⟨10.1109/ACCESS.2025.3568706⟩
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Determining Effective Temporal Windows for Rapeseed Detection Using Sentinel-1 Time Series and Machine Learning Algorithms

Saeideh Maleki , Nicolas Baghdadi , Sami Najem , Cassio F. Dantas , Hassan Bazzi et al.
Remote Sensing, 2024, 16 (3), pp.549. ⟨10.3390/rs16030549⟩
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A constrastive semi-supervised deep learning framework for land cover classification of satellite time series with limited labels

Dino Ienco , Raffaele Gaetano , Roberto Interdonato
Neurocomputing, 2024, 567, pp.127031. ⟨10.1016/j.neucom.2023.127031⟩
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Early Season Forecasting of Corn Yield at Field Level from Multi-Source Satellite Time Series Data

Johann Desloires , Dino Ienco , Antoine Botrel
Remote Sensing, 2024, 16 (9), pp.1573. ⟨10.3390/rs16091573⟩
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Machine Learning-Based Summer Crops Mapping Using Sentinel-1 and Sentinel-2 Images

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Multi-source deep-learning approach for automatic geomorphological mapping: the case of glacial moraines

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Geo-spatial Information Science, 2024, 16, pp.1-20. ⟨10.1080/10095020.2023.2292587⟩
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Reuse out-of-year data to enhance land cover mapping via feature disentanglement and contrastive learning

Cassio F. Dantas , Raffaele Gaetano , Claudia Paris , Dino Ienco
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 18, pp.1681-1694. ⟨10.1109/JSTARS.2024.3503756⟩
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Orthrus: multi-scale land cover mapping from satellite image time series via 2D encoding and convolutional neural network

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Neural Computing and Applications, 2024, 36, pp.19247-19265. ⟨10.1007/s00521-024-10186-2⟩
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Explaining the decisions and the functioning of a convolutional spatiotemporal land cover classifier with channel attention and redescription mining

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ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 215, pp.256-270. ⟨10.1016/j.isprsjprs.2024.06.021⟩
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Generation of country-scale canopy height maps over Gabon using deep learning and TanDEM-X InSAR data

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Remote Sensing of Environment, 2024, 311, pp.114270. ⟨10.1016/j.rse.2024.114270⟩
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Engineering Applications of Artificial Intelligence, 2023, 122, pp.106152. ⟨10.1016/j.engappai.2023.106152⟩
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Temporal-Domain Adaptation for Satellite Image Time-Series Land-Cover Mapping With Adversarial Learning and Spatially Aware Self-Training

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IEEE Access, 2023, 11, pp.20877-20884. ⟨10.1109/ACCESS.2023.3251194⟩
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Sentinel-2 images to assess soil surface characteristics over a rainfed Mediterranean cropping system

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CATENA, 2022, 213, pp.#106152. ⟨10.1016/j.catena.2022.106152⟩
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Dealing with multipositive unlabeled learning combining metric learning and deep clustering

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IEEE Access, 2022, 10, pp.51839 - 51849. ⟨10.1109/ACCESS.2022.3174590⟩
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Azza Abidi , Imed Riadh Farah , Y. Gbodjo , Dino Ienco , I. Farah
Remote Sensing Letters, 2022, 13 (2), pp.162-172. ⟨10.1080/2150704X.2021.2001071⟩
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ESA☆: A generic framework for semi-supervised inductive learning

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Neurocomputing, 2021, 447, pp.102-117. ⟨10.1016/j.neucom.2021.03.051⟩
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Remote Sensing of Environment, 2021, 265, 16 p. ⟨10.1016/j.rse.2021.112652⟩
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Attentive spatial temporal graph CNN for land cover mapping from multi temporal remote sensing data

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IEEE Access, 2021, 9, pp.23070-23082. ⟨10.1109/ACCESS.2021.3055554⟩
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International Journal of Remote Sensing, 2021, 42 (24), pp.9285-9308. ⟨10.1080/01431161.2021.1993465⟩
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Weakly Supervised learning for land cover mapping of satellite image time series via attention-based CNN

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IEEE Access, 2020, 8, pp.179547 - 179560. ⟨10.1109/ACCESS.2020.3024133⟩
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Remote Sensing, 2020, 12 (17), ⟨10.3390/rs12172814⟩
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Ecological Informatics, 2020, 59, pp.101110. ⟨10.1016/j.ecoinf.2020.101110⟩
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IEEE Geoscience and Remote Sensing Letters, 2020, 17 (11), pp.1909-1913. ⟨10.1109/LGRS.2019.2960625⟩
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Toward Spatio–Spectral Analysis of Sentinel-2 Time Series Data for Land Cover Mapping

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IEEE Geoscience and Remote Sensing Letters, 2020, 17 (2), pp.307-311. ⟨10.1109/LGRS.2019.2917788⟩
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Unsupervised Change Detection Analysis in Satellite Image Time Series using Deep Learning Combined with Graph-Based Approaches

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13, pp.1450-1466. ⟨10.1109/JSTARS.2020.2982631⟩
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DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn

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ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 149, pp.91-104. ⟨10.1016/j.isprsjprs.2019.01.011⟩
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Dino Ienco , R. Interdonato , R. Gaetano , Dinh Ho Tong Minh
ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 158, pp.11-22. ⟨10.1016/j.isprsjprs.2019.09.016⟩
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Assessment of congruence between co-occurrence and functional networks: A new framework for revealing community assembly rules

Gaëlle Legras , Nicolas Loiseau , Jean-Claude Gaertner , Jean-Christophe Poggiale , Dino Ienco et al.
Scientific Reports, 2019, 9 (1), pp.19996. ⟨10.1038/s41598-019-56515-7⟩
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Mapping irrigated areas using Sentinel-1 Time series in Catalonia, Spain

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Remote Sensing, 2019, 11 (15), pp.1836. ⟨10.3390/rs11151836⟩
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Detection of spatio-temporal evolutions on multi-annual satellite image time series: A clustering based approach

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International Journal of Applied Earth Observation and Geoinformation, 2019, 74, pp.103-119. ⟨10.1016/j.jag.2018.07.014⟩
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A Two-Branch CNN Architecture for Land Cover Classification of PAN and MS Imagery

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Remote Sensing, 2018, 10 (11), pp.1746. ⟨10.3390/rs10111746⟩
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Fuzzy extensions of the DBScan clustering algorithm

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Soft Computing, 2018, Methodologies and Application, 22 (5), pp.1719-1730. ⟨10.1007/s00500-016-2435-0⟩
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Object-oriented satellite image time series analysis using a graph-based representation

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Ecological Informatics, 2018, 43, pp.52-64. ⟨10.1016/j.ecoinf.2017.11.003⟩
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<formula> <tex>$M^3\text{Fusion}$</tex> </formula>: A Deep Learning Architecture for Multiscale Multimodal Multitemporal Satellite Data Fusion

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11 (12), pp.4939-4949. ⟨10.1109/JSTARS.2018.2876357⟩
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Deep Recurrent Neural Networks for Winter Vegetation Quality Mapping via Multitemporal SAR Sentinel-1

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IEEE Geoscience and Remote Sensing Letters, 2018, 15 (3), pp.464-468. ⟨10.1109/LGRS.2018.2794581⟩
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APPLICATION OF DEEP LEARNING OF MULTI-TEMPORAL SENTINEL-1 IMAGES FOR THE CLASSIFICATION OF COASTAL VEGETATION ZONE OF THE DANUBE DELTA

Simona Niculescu , Dino Ienco , Jenica Hanganu
ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018, XLII-3, pp.1311-1318. ⟨10.5194/isprs-archives-XLII-3-1311-2018⟩
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Mining Frequent Subgraphs in Multigraphs

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Information Sciences, 2018, 451-452, pp.50-66. ⟨10.1016/j.ins.2018.04.001⟩
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A graph-based approach to detect spatiotemporal dynamics in satellite image time series

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ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 130, pp.92-107. ⟨10.1016/j.isprsjprs.2017.05.013⟩
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Local Community Detection in Multilayer Networks

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Data Mining and Knowledge Discovery, 2017, ECML PKDD Conference 2017, 31 (5), pp.1444-1479. ⟨10.1007/s10618-017-0525-y⟩
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A Semi-Supervised Approach to the Detection and Characterization of Outliers in Categorical Data

Dino Ienco , Ruggero Pensa , Rosa Meo
IEEE Transactions on Neural Networks and Learning Systems, 2017, 28 (5), pp.1017-1029. ⟨10.1109/TNNLS.2016.2526063⟩
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Land Cover Classification via Multitemporal Spatial Data by Deep Recurrent Neural Networks

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IEEE Geoscience and Remote Sensing Letters, 2017, 14 (10), pp.1685-1689. ⟨10.1109/LGRS.2017.2728698⟩
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Positive and unlabeled learning in categorical data

Dino Ienco , Ruggero G. Pensa
Neurocomputing, 2016, 196 (july), pp.113 - 124. ⟨10.1016/j.neucom.2016.01.089⟩
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MultiLingMine 2016 - modeling, learning and mining for cross/multilinguality: proceedings of the first workshop on modeling, learning and mining for cross/multilinguality

Dino Ienco , M. Roche , S. Romeo , P. Rosso , A. Tagarelli
Sigir Forum, 2016, 50 (2), pp.89-95
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Combining transductive and active learning to improve object-based classification of remote sensing images

Fábio Nór Güttler , Dino Ienco , Pascal Poncelet , Maguelonne Teisseire
Remote Sensing Letters, 2016, 7 (4), pp.358-367. ⟨10.1080/2150704X.2016.1142678⟩
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User-driven geo-temporal density-based exploration of periodic and not periodic events reported in social networks

Paolo Arcaini , Gloria Bordogna , Dino Ienco , Simone Sterlacchini
Information Sciences, 2016, 340, pp.122-143. ⟨10.1016/j.ins.2016.01.014⟩
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Leveraging efficient indexing schema to support multigraph query answering

Dino Ienco , Vijay Ingalalli , Pascal Poncelet
Revue des Sciences et Technologies de l'Information - Série ISI : Ingénierie des Systèmes d'Information, 2016, 21 (3), pp.53-74. ⟨10.3166/isi.21.3.53-74⟩
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A quality-aware spatial data warehouse for querying hydroecological data

Soumia Lilia Berrahou , Nathalie Lalande , Eva Serrano , Guilhem Molla , Laure Berti-Équille et al.
Computers & Geosciences, 2015, 85 (part A), pp.126 - 135. ⟨10.1016/j.cageo.2015.09.012⟩
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Spatio-temporal data classification through multidimensional sequential patterns: Application to crop mapping in complex landscape

Yoann Pitarch , Dino Ienco , Elodie Vintrou , Agnès Bégué , Anne Laurent et al.
Engineering Applications of Artificial Intelligence, 2015, 37, pp.91-102. ⟨10.1016/j.engappai.2014.09.001⟩
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Clustering view-segmented documents via tensor modeling

S. Romeo , A. Tagarelli , Dino Ienco
Lecture Notes in Computer Science, 2014, 8502, pp.385-394. ⟨10.1007/978-3-319-08326-1_39⟩
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Animitex : Analyse d'Images fondée sur des Informations Textuelles

Mathieu Roche , Maguelonne Teisseire , Bruno Crémilleux , Pierre Gancarski , Christian Sallaberry et al.
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A contribution to the discovery of multidimensional patterns in healthcare trajectories

Elias Egho , Nicolas Jay , Chedy Raïssi , Dino Ienco , Pascal Poncelet et al.
Journal of Intelligent Information Systems, 2014, 42 (2), pp.283 - 305. ⟨10.1007/s10844-014-0309-4⟩
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Hierarchical Co-Clustering: Off-line and Incremental Approaches

Ruggero Pensa , Dino Ienco , Rosa Meo
Data Mining and Knowledge Discovery, 2014, 28 (1), pp.31-64. ⟨10.1007/s10618-012-0292-8⟩
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Data Mining, a promising tool for large-area cropland mapping

E. Vintrou , Dino Ienco , Agnès Bégué , Maguelonne Teisseire
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, 6 (5), pp.2132-2138. ⟨10.1109/JSTARS.2013.2238507⟩
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Parameter-less co-clustering for star-structured heterogeneous data

Dino Ienco , Céline Robardet , Ruggero G. Pensa , Rosa Meo
Data Mining and Knowledge Discovery, 2013, 26 (2), pp.217-254. ⟨10.1007/s10618-012-0248-z⟩
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The Meme Ranking Problem: Maximizing Microblogging Virality

Francesco Bonchi , Carlos Castillo , Dino Ienco
Journal of Intelligent Information Systems, 2013, 40 (2), pp.211-239. ⟨10.1007/s10844-011-0181-4⟩
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LODE: A distance-based classifier built on ensembles of positive and negative observations

Rosa Meo , Dipankar Bachar , Dino Ienco
Pattern Recognition, 2012, 45 (4), pp.1409-1425. ⟨10.1016/j.patcog.2011.10.015⟩
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Cartographie de l’habitat de reproduction du tétras-lyre (Lyrurus tetrix) dans les Alpes françaises

Alexandre Defossez , Samuel Alleaume , Marc Montadert , Dino Ienco , Sandra Luque et al.
INRAE; OFB, Office Français de la Biodiversité. 2024
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[Rapport Technique] IRSTEA. 2015, pp.31
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Presidential Election 2012: How French politicians tweet?

Flavien Bouillot , Dino Ienco , Stan Matwin , Pascal Poncelet , Mathieu Roche
RR-12011, 2012
Rapport lirmm-00688651 v1
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Foundations and state of the art

Nathalie Mitton , Ludovic Brossard , Tassadit Bouadi , Frédérick Garcia , Romain Gautron et al.
Agriculture 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
Chapitre d'ouvrage hal-03609470 v2
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Querying RDF Data: A Multigraph Based Approach

Vijay Ingalalli , Dino Ienco , Pascal Poncelet
Olivier 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⟩
Chapitre d'ouvrage lirmm-01910660 v1

Discovery Science - 25th International Conference, DS 2022, Montpellier, France, October 10-12, 2022, Proceedings

Pascal Poncelet , Dino Ienco
DS 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⟩
Proceedings/Recueil des communications lirmm-04206262 v1

Towards combining satellite imagery and VGI for urban LULC classification

Dino Ienco , K. Ose , C. Weber
2019 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⟩
Proceedings/Recueil des communications hal-02609706 v1

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.

Dino Ienco , Mathieu Roche , Salvatore Romeo , Paolo Rosso , Andrea Tagarelli
MultiLingMine: Modeling, Learning and Mining for Cross/Multilinguality, Mar 2016, Padova, Italy. 1589, , 2016, CEUR Workshop Proceedings
Proceedings/Recueil des communications lirmm-01382023 v1
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Mining and learning from spatio-temporal data: examples and perspectives

Dino Ienco
Environmental Sciences. HDR en Informatique, Université de Montpellier, 2016
HDR tel-02605252 v1

Process for identifying rare events

Renaud Cezar , Dino Ienco , André Mas , Florent Masseglia , Pascal Poncelet et al.
United States, Patent n° : EP13153512A; EP2014051963W. 2013
Brevet lirmm-00913008 v1