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Pierre Gançarski
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2020 – today
- 2024
- [c64]Emmanuelle Claeys, Myriam Maumy-Bertrand, Pierre Gançarski:
Time Series Clustering for Enhanced Dynamic Allocation in A/B Testing. ECML/PKDD (9) 2024: 351-367 - 2023
- [j37]Mihailo Obrenovic
, Thomas Andrew Lampert, Milos R. Ivanovic, Pierre Gançarski:
Learning domain invariant representations of heterogeneous image data. Mach. Learn. 112(10): 3659-3684 (2023) - [j36]Hussein El Amouri
Constrained DTW preserving shapelets for explainable time-series clustering. Pattern Recognit. 143: 109804 (2023) - [j35]Emmanuelle Claeys
Dynamic Allocation Optimization in A/B-Tests Using Classification-Based Preprocessing. IEEE Trans. Knowl. Data Eng. 35(1): 335-349 (2023) - [c63]Mihailo Obrenovic
Constrained-HIDA: Heterogeneous Image Domain Adaptation Guided by Constraints. ECML/PKDD (5) 2023: 443-458 - 2022
- [j34]Baptiste Lafabregue
End-to-end deep representation learning for time series clustering: a comparative study. Data Min. Knowl. Discov. 36(1): 29-81 (2022) - [j33]Zouhayra Ayadi, Wadii Boulila
Resolution methods for constraint satisfaction problem in remote sensing field: A survey of static and dynamic algorithms. Ecol. Informatics 69: 101607 (2022) - [j32]Corinne Grac, Agnès Braud, Pierre Gançarski, Agnès Herrmann, Florence Le Ber
Comparing the physico-chemistry dynamics of running waters (North-East of France) based on sequence clustering. Ecol. Informatics 72: 101921 (2022) - [c62]Baptiste Lafabregue, Pierre Gançarski, Jonathan Weber, Germain Forestier:
Incremental constrained clustering with application to remote sensing images time series. ICDM (Workshops) 2022: 814-823 - [c61]Zeeshan Nisar, Jelica Vasiljevic
Towards Measuring Domain Shift in Histopathological Stain Translation in an Unsupervised Manner. ISBI 2022: 1-5 - [c60]Hussein El Amouri
CDPS: Constrained DTW-Preserving Shapelets. ECML/PKDD (1) 2022: 21-37 - [i3]Zeeshan Nisar, Jelica Vasiljevic, Pierre Gançarski, Thomas Andrew Lampert:
Towards Measuring Domain Shift in Histopathological Stain Translation in an Unsupervised Manner. CoRR abs/2205.04368 (2022) - 2021
- [j31]Kaouthar Driss
Mining frequent approximate patterns in large networks. Int. J. Imaging Syst. Technol. 31(3): 1265-1279 (2021) - [j30]Abdoul-Djawadou Salaou, Daniela E. Damian, Casper Lassenius, Dragos Voda, Pierre Gançarski:
Archetypes of delay: An analysis of online developer conversations on delayed work items in IBM Jazz. Inf. Softw. Technol. 129: 106435 (2021) - [j29]Jimmy Francky Randrianasoa
Supervised quality evaluation of binary partition trees for object segmentation. Pattern Recognit. 111: 107667 (2021) - [c59]Agnès Braud, Pierre Gançarski, Corinne Grac, Agnès Hermann, Florence Le Ber, Harrison Vernier:
Classification de séries temporelles hétérogènes pour le suivi de l'état des cours d'eau. EGC 2021: 71-82 - [c58]Baptiste Lafabregue
Grad Centroid Activation Mapping for Convolutional Neural Networks. ICTAI 2021: 184-191 - [c57]Mihailo Obrenovic, Thomas Andrew Lampert, François Monde-Kossi, Milos R. Ivanovic, Pierre Gançarski:
SS-HIDA: Semi-Supervised Heterogeneous Image Domain Adaptation. MACLEAN@PKDD/ECML 2021 - 2020
- [c56]Emmanuelle Claeys, Pierre Gançarski, Myriam Maumy-Bertrand:
Intégration des séries temporelles dans les A/B-Tests. EGC 2020: 121-132 - [c55]Pierre Gançarski, Baptiste Lafabregue, Abdoul-Djawadou Salaou, Harrison Vernier:
FODOMUST - Une plateforme de clustering collaboratif sous contraintes incrémental de séries temporelles. EGC 2020: 507-514 - [p2]Pierre Gançarski, Thi-Bich-Hanh Dao
Constrained Clustering: Current and New Trends. A Guided Tour of Artificial Intelligence Research (2) (II) 2020: 447-484
2010 – 2019
- 2019
- [j28]Thomas Andrew Lampert, Baptiste Lafabregue
Constrained Distance-Based Clustering for Satellite Image Time-Series. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(11): 4606-4621 (2019) - [c54]Thomas Andrew Lampert, Baptiste Lafabregue
Constrained Distance based K-Means Clustering for Satellite Image Time-Series. IGARSS 2019: 2419-2422 - [c53]Baptiste Lafabregue, Jonathan Weber, Pierre Gançarski, Germain Forestier:
Deep Constrained Clustering applied to Satellite Image Time Series. MACLEAN@PKDD/ECML 2019 - 2018
- [j27]Thomas Andrew Lampert, Thi-Bich-Hanh Dao
Constrained distance based clustering for time-series: a comparative and experimental study. Data Min. Knowl. Discov. 32(6): 1663-1707 (2018) - [j26]Antoine Cornuéjols, Cédric Wemmert, Pierre Gançarski, Younès Bennani
Collaborative clustering: Why, when, what and how. Inf. Fusion 39: 81-95 (2018) - [j25]Andrés Troya-Galvis, Pierre Gançarski, Laure Berti-Équille
Remote sensing image analysis by aggregation of segmentation-classification collaborative agents. Pattern Recognit. 73: 259-274 (2018) - [c52]Emmanuelle Claeys, Pierre Gançarski, Myriam Maumy-Bertrand:
Approche contextuelle par régression pour les tests A/B. EGC 2018: 269-274 - 2017
- [j24]Andrés Troya-Galvis, Pierre Gançarski, Laure Berti-Équille:
Interactions segmentation-classification dans un cadre multi-paradigme pour l'analyse d'images de télédétection. Rev. d'Intelligence Artif. 31(1-2): 133-152 (2017) - [c51]Emmanuelle Claeys, Pierre Gançarski, Myriam Maumy-Bertrand, Hubert Wassner:
Approche paramétrique de bandits pour le test A/B. APIA 2017: 19-25 - [c50]Andrés Troya-Galvis, Pierre Gançarski, Isabelle Mougenot, Laure Berti-Équille:
Sur l'évaluation et l'élaboration d'un jeu de données de référence de bonne qualité en télédétection. EGC 2017: 393-398 - [c49]Emmanuelle Claeys, Pierre Gançarski, Myriam Maumy-Bertrand, Hubert Wassner:
Conception d'un modèle généraliste pour l'évaluation d'un test A/B. EGC 2017: 423-424 - [c48]Jimmy Francky Randrianasoa
Evaluating the quality of binary partition trees based on uncertain semantic ground-truth for image segmentation. ICIP 2017: 3874-3878 - [c47]Emmanuelle Claeys, Pierre Gançarski, Myriam Maumy-Bertrand
Regression Tree for Bandits Models in A/B Testing. IDA 2017: 52-62 - 2016
- [j23]Pierre Gançarski, Anne Puissant
Use of symbolic dynamic time warping in hierarchical clustering of urban fabric evolutions extracted from spatiotemporal topographic databases. AI Commun. 29(6): 733-746 (2016) - [j22]Thomas Andrew Lampert
An Empirical Study Into Annotator Agreement, Ground Truth Estimation, and Algorithm Evaluation. IEEE Trans. Image Process. 25(6): 2557-2572 (2016) - [c46]Pedro Chahuara, Thomas Andrew Lampert, Pierre Gançarski:
Retrieving and Ranking Similar Questions from Question-Answer Archives Using Topic Modelling and Topic Distribution Regression. TPDL 2016: 41-53 - [c45]Andrés Troya-Galvis, Pierre Gançarski, Laure Berti-Équille:
A Collaborative Framework for Joint Segmentation and Classification of Remote Sensing Images. EGC (best of volume) 2016: 127-145 - [c44]Andrés Troya-Galvis, Pierre Gançarski, Laure Berti-Équille:
Un cadre collaboratif pour la segmentation et la classification d'images de télédétection. EGC 2016: 297-308 - [c43]Pierre Gançarski, Abdoul-Djawadou Salaou:
FODOMUST: une plateforme pour la fouille de données multistratégie multitemporelle. EGC 2016: 481-486 - [c42]Andres Troya-Galvis, Pierre Gançarski, Laure Berti-Équille
Collaborative segmentation and classification for remote sensing image analysis. ICPR 2016: 829-834 - [i2]Pedro Chahuara, Thomas Andrew Lampert, Pierre Gançarski:
Retrieving and Ranking Similar Questions from Question-Answer Archives Using Topic Modelling and Topic Distribution Regression. CoRR abs/1606.03783 (2016) - 2015
- [j21]Andres Troya-Galvis, Pierre Gançarski, Nicolas Passat, Laure Berti-Équille
Unsupervised Quantification of Under- and Over-Segmentation for Object-Based Remote Sensing Image Analysis. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(5): 1936-1945 (2015) - [c41]Jérémie Sublime
Semantic rich ICM algorithm for VHR satellite images segmentation. MVA 2015: 45-48 - [c40]Nistor Grozavu, Nicoleta Rogovschi, Guénaël Cabanes
VHR satellite image segmentation based on topological unsupervised learning. MVA 2015: 543-546 - 2014
- [j20]Mathieu Roche, Maguelonne Teisseire, Bruno Crémilleux, Pierre Gançarski, Christian Sallaberry:
ANIMITEX. Analyse d'images fondée sur des informations textuelles. Ingénierie des Systèmes d Inf. 19(3): 163-167 (2014) - [j19]Thomas Andrew Lampert, Pierre Gançarski:
The bane of skew - Uncertain ranks and unrepresentative precision. Mach. Learn. 97(1-2): 5-32 (2014) - [c39]Alban Meffre, Nicolas Lachiche, Pierre Gançarski, Christophe Collet:
Détection de situations à risque basée sur des détecteurs de mouvement à domicile pour les personnes dépendantes. EGC 2014: 577-580 - 2013
- [j18]Camille Kurtz
A hierarchical semantic-based distance for nominal histogram comparison. Data Knowl. Eng. 87: 206-225 (2013) - [c38]Cédric Wemmert, Juliane M. Kruger, Germain Forestier
Stain unmixing in brightfield multiplexed immunohistochemistry. ICIP 2013: 1125-1129 - [c37]François Petitjean
Detecting land-cover modifications from multi-resolution satellite image time series. IGARSS 2013: 3447-3450 - [i1]Thomas Andrew Lampert, André Stumpf, Pierre Gançarski:
An Empirical Study into Annotator Agreement, Ground Truth Estimation, and Algorithm Evaluation. CoRR abs/1307.0426 (2013) - 2012
- [j17]Camille Kurtz
Extraction of complex patterns from multiresolution remote sensing images: A hierarchical top-down methodology. Pattern Recognit. 45(2): 685-706 (2012) - [j16]François Petitjean
Spatio-temporal reasoning for the classification of satellite image time series. Pattern Recognit. Lett. 33(13): 1805-1815 (2012) - [j15]François Petitjean
Summarizing a set of time series by averaging: From Steiner sequence to compact multiple alignment. Theor. Comput. Sci. 414(1): 76-91 (2012) - [j14]François Petitjean
Satellite Image Time Series Analysis Under Time Warping. IEEE Trans. Geosci. Remote. Sens. 50(8): 3081-3095 (2012) - [j13]Germain Forestier
Knowledge-based region labeling for remote sensing image interpretation. Comput. Environ. Urban Syst. 36(5): 470-480 (2012) - [c36]Patrice Roy
Generic architecture for ambient intelligence based on an organizational centered multi-agent approach. UbiComp 2012: 786-789 - [c35]Camille Kurtz
A histogram semantic-based distance for multiresolution image classification. ICIP 2012: 1157-1160 - [c34]Alban Meffre, Christophe Collet, Nicolas Lachiche
Real-Time Fall Detection Method Based on Hidden Markov Modelling. ICISP 2012: 521-530 - [c33]Camille Kurtz
Domain adaptation for the extraction of complex urban patterns from multiresolution satellite images. IGARSS 2012: 1773-1776 - [c32]Jonathan Weber
Towards efficient satellite image time series analysis: Combination of dynamic time warping and quasi-flat zones. IGARSS 2012: 4387-4390 - [c31]François Petitjean
Introducing prior knowledge in temporal distances for Satellite Image Time Series analysis. IGARSS 2012: 5426-5429 - [c30]François Petitjean
Monitoring urban sprawl from Satellite Image Time Series. IGARSS 2012: 5963-5966 - 2011
- [j12]François Petitjean
Discovering Significant Evolution Patterns from Satellite Image Time Series. Int. J. Neural Syst. 21(6): 475-489 (2011) - [j11]François Petitjean
A global averaging method for dynamic time warping, with applications to clustering. Pattern Recognit. 44(3): 678-693 (2011) - [c29]François Petitjean, Florent Masseglia, Pierre Gançarski:
Découverte de motifs d'évolutions significatifs dans les séries temporelles d'images satellites. EGC 2011: 665-676 - [c28]Camille Kurtz
A context-based approach for the classification of Satellite Image Time Series. IGARSS 2011: 495-498 - [c27]François Petitjean
Temporal domain adaptation under time warping. IGARSS 2011: 3578-3581 - [c26]Jonathan Weber, Sébastien Lefèvre, Pierre Gançarski:
Interactive video segmentation based on quasi-flat zones. ISPA 2011: 265-270 - [c25]Jonathan Weber
Spatio-temporal Quasi-Flat Zones for Morphological Video Segmentation. ISMM 2011: 178-189 - [c24]Camille Kurtz
Hierarchical Segmentation of Multiresolution Remote Sensing Images. ISMM 2011: 343-354 - [c23]Camille Kurtz
An interactive approach for extraction of urban patterns from multisource images. JURSE 2011: 321-324 - 2010
- [j10]Germain Forestier
Collaborative clustering with background knowledge. Data Knowl. Eng. 69(2): 211-228 (2010) - [c22]Germain Forestier, Cédric Wemmert, Pierre Gançarski:
Comparaison de critères de pureté pour l'intégration de connaissances en clustering semi-supervisé. EGC 2010: 127-132 - [c21]François Petitjean
Analysing Satellite Image Time Series by Means of Pattern Mining. IDEAL 2010: 45-52 - [c20]Germain Forestier
Towards conflict resolution in collaborative clustering. IEEE Conf. of Intelligent Systems 2010: 361-366 - [c19]Germain Forestier
Background Knowledge Integration in Clustering Using Purity Indexes. KSEM 2010: 28-38 - [c18]Jonathan Weber
Video Object Mining: Issues and Perspectives. ICSC 2010: 85-90 - [e2]Brigitte Trousse, Pierre Gançarski, Omar Boussaïd:
Fouille de données complexes. RNTI E-18, Hermann-Éditions 2010, ISBN 978-2-85428-917-6 [contents]
2000 – 2009
- 2009
- [j9]Cédric Wemmert, Anne Puissant
Multiresolution Remote Sensing Image Clustering. IEEE Geosci. Remote. Sens. Lett. 6(3): 533-537 (2009) - [c17]Germain Forestier
Mining Multiple Satellite Sensor Data Using Collaborative Clustering. ICDM Workshops 2009: 501-506 - [p1]Marinette Bouet, Pierre Gançarski, Marie-Aude Aufaure, Omar Boussaid:
Pattern Mining and Clustering on Image Databases. Database Technologies: Concepts, Methodologies, Tools, and Applications 2009: 60-85 - [e1]Jean-Gabriel Ganascia, Pierre Gançarski:
Extraction et gestion des connaissances (EGC'2009), Actes, Strasbourg, France, 27 au 30 janvier 2009. Revue des Nouvelles Technologies de l'Information RNTI-E-15, Cépaduès-Éditions 2009, ISBN 978-2-85428-878-0 [contents] - 2008
- [j8]Germain Forestier
Multisource Images Analysis Using Collaborative Clustering. EURASIP J. Adv. Signal Process. 2008 (2008) - [j7]Pierre Gançarski, Alexandre Blansché, Annett Wania
Comparison between two coevolutionary feature weighting algorithms in clustering. Pattern Recognit. 41(3): 983-994 (2008) - [j6]Pierre Gançarski, Alexandre Blansché:
Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in K-means-Based Algorithms. IEEE Trans. Evol. Comput. 12(5): 617-629 (2008) - [j5]Stéphane Genaud
Exploitation of a parallel clustering algorithm on commodity hardware with P2P-MPI. J. Supercomput. 43(1): 21-41 (2008) - [c16]Germain Forestier
An Evolutionary Approach for Ontology Driven Image Interpretation. EvoWorkshops 2008: 295-304 - [c15]Germain Forestier, Sébastien Derivaux, Cédric Wemmert, Pierre Gançarski:
Interprétation d'images basée sur une approche évolutive guidée par une ontologie. EGC 2008: 469-474 - [c14]Germain Forestier
Semi-supervised Collaborative Clustering with Partial Background Knowledge. ICDM Workshops 2008: 211-217 - [c13]Germain Forestier
On Combining Unsupervised Classification and Ontology Knowledge. IGARSS (4) 2008: 395-398 - 2007
- [j4]Pierre Gançarski, Cédric Wemmert:
Collaborative multi-step mono-level multi-strategy classification. Multim. Tools Appl. 35(1): 1-27 (2007) - [c12]Rémy Brisson, Omar Boussaid, Pierre Gançarski, Anne Puissant, Nicolas Durand:
Navigation et appariement d'objets géographiques dans une ontologie. EGC 2007: 391-396 - [c11]Nicolas Durand
Ontology-Based Object Recognition for Remote Sensing Image Interpretation. ICTAI (1) 2007: 472-479 - 2006
- [j3]Omar Boussaid, Pierre Gançarski, Florent Masseglia, Brigitte Trousse, Dominique Desbois:
Notes de lecture : Fouille de Données Complexes. Monde des Util. Anal. Données 34: 117-118 (2006) - [j2]Alexandre Blansché, Pierre Gançarski, Jerzy J. Korczak
MACLAW: A modular approach for clustering with local attribute weighting. Pattern Recognit. Lett. 27(11): 1299-1306 (2006) - [c10]Alexandre Blansché, Annett Wania, Pierre Gançarski:
Comparison of MACLAW with several attribute selection methods for classification in hyperspectral images. ICDM Workshops 2006: 231-236 - 2005
- [c9]Alexandre Blansché, Pierre Gançarski, Jerzy J. Korczak
A Coevolutionary Approach for Clustering with Feature Weighting Application to Image Analysis. EvoWorkshops 2005: 254-263 - [c8]Alexandre Blansché, Pierre Gançarski, Jerzy Korczak:
Representative Individuals Initialisation in Cooperative Coevolution. IICAI 2005: 2748-2758 - [c7]Pierre Gançarski, Cédric Wemmert:
Collaborative multi-strategy classification: application to per-pixel analysis of images. MDM@KDD 2005: 15-22 - [c6]Alexandre Blansché, Pierre Gançarski, Jerzy J. Korczak
Genetic Algorithms for Feature Weighting: Evolution vs. Coevolution and Darwin vs. Lamarck. MICAI 2005: 682-691 - 2004
- [c5]Alexandre Blansché, Pierre Gançarski:
Sélection d'attributs et classification d'objets complexes. EGC 2004: 203 - 2000
- [j1]Cédric Wemmert, Pierre Gançarski, Jerzy J. Korczak:
A Collaborative Approach to Combine Multiple Learning Methods. Int. J. Artif. Intell. Tools 9(1): 59-78 (2000)
1990 – 1999
- 1999
- [c4]Cédric Wemmert, Pierre Gançarski, Jerzy Korczak:
An Unsupervised Collaborative Learning Method to Refine Classification Hierarchies. ICTAI 1999: 263-270 - 1995
- [c3]Alain Ketterlin, Pierre Gançarski, Jerzy J. Korczak:
Hierarchical Clustering of Composite Objects with a Variable Number of Components. AISTATS 1995: 229-238 - [c2]Alain Ketterlin, Pierre Gançarski, Jerzy J. Korczak:
Conceptual Clustering in Structured Databases: A Practical Approach. KDD 1995: 180-185 - 1990
- [c1]Pierre Gançarski:
A Generative System for Interactive Animation Based on Reactive System Semantics and on Actor Semantics. GI Jahrestagung (2) 1990: 579-588
Coauthor Index
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