Jérémie Sublime
Publications
Publications
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MULTI-MAP FUSION FOR WEAKLY SUPERVISED DISEASE LOCALIZATION FROM GLOBALLY ASSIGNED DIAGNOSTIC LABELS IN BRAIN MRIThe IEEE International Symposium on Biomedical Imaging, IEEE, Apr 2026, London, GB, United Kingdom |
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Application of explainable AI to healthcare: a review ⋆IDDM’24: 7th International Conference on Informatics & Data-Driven Medicine, Nov 2024, Birmingham (UK), United Kingdom |
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DEEP NEURAL NETWORKS COMPARISON FOR MRI SEGMENTATION OF THE BRAINSTEMThe 21st IEEE International Symposium on Biomedical Imaging, IEEE, May 2024, Athens, Greece |
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Artificial Intelligence for Methane Mitigation : Through an Automated Determination of Oil and Gas Methane Emissions ProfilesNeurIPS, Dec 2023, Nouvelle-Orléans, Louisiane, United States |
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Context-aware Attention U-Net for the segmentation of pores in Lamina Cribrosa using partial points annotation21st IEEE International Conference on Machine Learning and Applications (IEEE ICMLA'22), Dec 2022, Bahamas, Bahamas |
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Deep Cooperative Reconstruction with Security Constraints in multi-view environmentsICDMW 2020, Nov 2020, Online, Italy |
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A new Information theory based clustering fusion method for multi-view representations of text documents22nd International Conference on Human-Computer Interaction (HCI 2020), Jul 2020, Copenhague, Denmark |
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An Information Theory based Approach to Multisource ClusteringTwenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}, Jul 2018, Stockholm, Sweden. ⟨10.24963/ijcai.2018/358⟩ |
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Collaborative clustering based on Algorithmic Information TheoryCAp ( Conférence sur l'Apprentissage Automatique ) 2017, Jun 2017, Grenoble, France |
Analysis of the influence of diversity in collaborative and multi-view clusteringIJCNN-2017 (Int. Joint Conf. on Neural Networks), May 2017, Anchorage, United States |
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Collaborative learning using topographic mapsAAFD and SFC'16 Conférence Internationale Francophone "Science des données. Défis Mathématiques et algorithmiques", May 2016, Marrakech, Morocco |
Vertical collaborative clustering using generative topographic maps7th International Conference of Soft Computing and Pattern Recognition (SoCPaR), Nov 2015, Fukuoka, Japan. pp.199-204, ⟨10.1109/SOCPAR.2015.7492807⟩ |
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Collaborative-Based Multi-scale Clustering in Very High Resolution Satellite ImagesInternational Conference on Neural Information (ICONIP) Processing, Oct 2016, Tokyo, Japan. pp.148-155, ⟨10.1007/978-3-319-46675-0_17⟩ |
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Semantic rich ICM algorithm for VHR satellite images segmentation14th IAPR International Conference on Machine Vision Applications (MVA), May 2015, Tokyo, Japan. pp.15292961, ⟨10.1109/MVA.2015.7153129⟩ |
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Collaborative Clustering with Heterogeneous AlgorithmsInternational Joint Conference on Neural Networks (IJCNN), Jul 2015, Killarney, Ireland. 8 p |
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Collaborative Clustering with Heterogeneous AlgorithmsIJCNN 2015, Jul 2015, Killarney, Ireland. pp.8 |
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Un nouveau modèle d’énergie pour les champs aléatoires de Markov cachés21. Rencontres de la Société Francophone de Classification SFC'14, 2014, Rabat, Maroc |
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A new energy model for the Hidden Markov Random Fields21. International Conference on Neural Information Processing (ICONIP 2014), Nov 2014, kuching, Malaysia |
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Clustering collaboratif incrémentalConférence Francophone d'Apprentissage ( CAP2014 ), Jul 2014, Saint Etienne, France |
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Rethinking Collaborative Clustering: A Practical and Theoretical Study within the Realm of Multi-View ClusteringWitold Pedrycz and Shyi-Ming Chen. Recent Advancements in Multi-View Data Analytics, Studies in Big Data 106, 2022 |
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Unsupervised Change Detection using Joint Autoencoders for Age-Related Macular Degeneration ProgressionSpringer. ICANN 2020, Part II, 2, In press, LNCS 12397 |
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Change Detection in Satellite Images using Reconstruction Errors of Joint AutoencodersArtificial Neural Networks and Machine Learning – ICANN 2019: Image Processing, pp.637-648, 2019, ⟨10.1007/978-3-030-30508-6_50⟩ |
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Contributions to modern unsupervised learning: Case studies of multi-view clustering and unsupervised Deep LearningMachine Learning [cs.LG]. Sorbonne Université, 2021 |