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Jérémie Sublime
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2020 – today
- 2024
- [j13]Jérémie Sublime:
The AI Race: Why Current Neural Network-based Architectures are a Poor Basis for Artificial General Intelligence. J. Artif. Intell. Res. 79: 41-67 (2024) - [c25]Nan Ding, Florence Rossant, Hélène Urien, Jérémie Sublime, Paul Bastelica, Christophe Baudouin, Michel Pâques:
A Complete Method for the 3D Reconstruction of Axonal Pathways from 2 Orthogonal 3D OCT Images of the Lamina Cribrosa. ICASSP 2024: 2360-2364 - [c24]Jade Eva Guisiano, Domenico Barretta, Éric Moulines, Thomas Lauvaux, Jérémie Sublime:
Object Detection Models Sensitivity & Robustness to Satellite-based Adversarial Attacks. IGARSS 2024: 7844-7848 - [c23]Seoyoung Oh, Mélanie Pélégrini-Issac, Hélène Urien, Véronique Marchand-Pauvert, Jérémie Sublime:
Deep Neural Networks Comparison for MRI Segmentation of the Brainstem. ISBI 2024: 1-5 - 2023
- [j12]Juan Zamora, Jérémie Sublime:
An Ensemble and Multi-View Clustering Method Based on Kolmogorov Complexity. Entropy 25(2): 371 (2023) - [c22]Jade Eva Guisiano, Éric Moulines, Thomas Lauvaux, Jérémie Sublime:
Oil and Gas Automatic Infrastructure Mapping: Leveraging High-Resolution Satellite Imagery Through Fine-Tuning of Object Detection Models. ICONIP (12) 2023: 442-458 - [c21]Nan Ding, Florence Rossant, Hélène Urien, Jérémie Sublime, Michel Pâques:
3D Orthogonal SD-OCT Volumes Registration for the Enhancement of Pores in Lamina Cribrosa. ISBI 2023: 1-5 - 2022
- [j11]Ana Flávia dos Reis, Yahia Medjahdi, Bruno Sens Chang, Jérémie Sublime, Glauber Brante, Faouzi Bader:
Low Complexity LSTM-NN-Based Receiver for Vehicular Communications in the Presence of High-Power Amplifier Distortions. IEEE Access 10: 121985-122000 (2022) - [c20]Nan Ding, Hélène Urien, Florence Rossant, Jérémie Sublime, Michel Pâques:
Context-aware Attention U-Net for the segmentation of pores in Lamina Cribrosa using partial points annotation. ICMLA 2022: 537-542 - 2021
- [b2]Jérémie Sublime:
Contributions to modern unsupervised learning: Case studies of multi-view clustering and unsupervised Deep Learning. (Contributions à l'apprentissage non-supervisé moderne: Applications aux cas du clustering multi-vue et de l'apprentissage profond non-supervisé). Sorbonne University, France, 2021 - [j10]Clément Royer, Jérémie Sublime, Florence Rossant, Michel Pâques:
Unsupervised Approaches for the Segmentation of Dry ARMD Lesions in Eye Fundus cSLO Images. J. Imaging 7(8): 143 (2021) - 2020
- [j9]Guillaume Dupont, Ekaterina Kalinicheva, Jérémie Sublime, Florence Rossant, Michel Pâques:
Analyzing Age-Related Macular Degeneration Progression in Patients with Geographic Atrophy Using Joint Autoencoders for Unsupervised Change Detection. J. Imaging 6(7): 57 (2020) - [j8]Ekaterina Kalinicheva, Jérémie Sublime, Maria Trocan:
Unsupervised Satellite Image Time Series Clustering Using Object-Based Approaches and 3D Convolutional Autoencoder. Remote. Sens. 12(11): 1816 (2020) - [j7]Ekaterina Kalinicheva, Dino Ienco, Jérémie Sublime, Maria Trocan:
Unsupervised Change Detection Analysis in Satellite Image Time Series Using Deep Learning Combined With Graph-Based Approaches. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 1450-1466 (2020) - [c19]Juan Zamora, Jérémie Sublime:
A New Information Theory Based Clustering Fusion Method for Multi-view Representations of Text Documents. HCI (14) 2020: 156-167 - [c18]Guillaume Dupont, Ekaterina Kalinicheva, Jérémie Sublime, Florence Rossant, Michel Pâques:
Unsupervised Change Detection Using Joint Autoencoders for Age-Related Macular Degeneration Progression. ICANN (2) 2020: 813-824 - [c17]Denis Maurel, Sylvain Lefebvre, Jérémie Sublime:
Deep Cooperative Reconstruction with Security Constraints in multi-view environments. ICDM (Workshops) 2020: 579-588
2010 – 2019
- 2019
- [j6]Jérémie Sublime, Guénaël Cabanes, Basarab Matei:
Study on the Influence of Diversity and Quality in Entropy Based Collaborative Clustering. Entropy 21(10): 951 (2019) - [j5]Jérémie Sublime, Ekaterina Kalinicheva:
Automatic Post-Disaster Damage Mapping Using Deep-Learning Techniques for Change Detection: Case Study of the Tohoku Tsunami. Remote. Sens. 11(9): 1123 (2019) - [c16]Jérémie Sublime:
Incremental Collaborative Clustering Using Information Theory and Information Compression. FSDM 2019: 457-464 - [c15]Ekaterina Kalinicheva, Jérémie Sublime, Maria Trocan:
Change Detection in Satellite Images Using Reconstruction Errors of Joint Autoencoders. ICANN (3) 2019: 637-648 - [c14]Ekaterina Kalinicheva, Jérémie Sublime, Maria Trocan:
Object-Based Change Detection in Satellite Images Combined with Neural Network Autoencoder Feature Extraction. IPTA 2019: 1-6 - 2018
- [c13]Denis Maurel, Jérémie Sublime, Sylvain Lefebvre:
Cartes Auto-Organisatrices Incrémentales appliquées au Clustering Collaboratif. EGC 2018: 403-408 - [c12]Ekaterina Kalinicheva, Jérémie Sublime, Maria Trocan:
Neural Network Autoencoder for Change Detection in Satellite Image Time Series. ICECS 2018: 641-642 - [c11]Pierre-Alexandre Murena, Jérémie Sublime, Basarab Matei, Antoine Cornuéjols:
An Information Theory based Approach to Multisource Clustering. IJCAI 2018: 2581-2587 - [c10]Jérémie Sublime, Sylvain Lefebvre:
Collaborative Clustering through Constrained Networks using Bandit Optimization. IJCNN 2018: 1-8 - [c9]Jérémie Sublime, Denis Maurel, Nistor Grozavu, Basarab Matei, Younès Bennani:
Optimizing exchange confidence during collaborative clustering. IJCNN 2018: 1-8 - 2017
- [j4]Jérémie Sublime, Basarab Matei, Guénaël Cabanes, Nistor Grozavu, Younès Bennani, Antoine Cornuéjols:
Entropy based probabilistic collaborative clustering. Pattern Recognit. 72: 144-157 (2017) - [j3]Jérémie Sublime, Andrés Troya-Galvis, Anne Puissant:
Multi-Scale Analysis of Very High Resolution Satellite Images Using Unsupervised Techniques. Remote. Sens. 9(5): 495 (2017) - [c8]Denis Maurel, Jérémie Sublime, Sylvain Lefebvre:
Incremental Self-Organizing Maps for Collaborative Clustering. ICONIP (1) 2017: 497-504 - [c7]Jérémie Sublime, Basarab Matei, Pierre-Alexandre Murena:
Analysis of the influence of diversity in collaborative and multi-view clustering. IJCNN 2017: 4126-4133 - 2016
- [b1]Jérémie Sublime:
Contributions to collaborative clustering and its potential applications on very high resolution satellite images. (Contributions au clustering collaboratif et à ses potentielles applications en imagerie à très haute résolution). University of Paris-Saclay, France, 2016 - [c6]Jérémie Sublime, Antoine Cornuéjols, Younès Bennani:
Collaborative-Based Multi-scale Clustering in Very High Resolution Satellite Images. ICONIP (3) 2016: 148-155 - 2015
- [j2]Jérémie Sublime, Nistor Grozavu, Guénaël Cabanes, Younès Bennani, Antoine Cornuéjols:
From horizontal to vertical collaborative clustering using generative topographic maps. Int. J. Hybrid Intell. Syst. 12(4): 245-256 (2015) - [c5]Jérémie Sublime, Younès Bennani, Antoine Cornuéjols:
Un algorithme ICM basé sur la compacité pour la segmentation des images satellites à très haute résolution. EGC 2015: 191-196 - [c4]Jérémie Sublime, Nistor Grozavu, Younès Bennani, Antoine Cornuéjols:
Collaborative clustering with heterogeneous algorithms. IJCNN 2015: 1-8 - [c3]Jérémie Sublime, Andres Troya-Galvis, Younès Bennani, Antoine Cornuéjols, Pierre Gançarski:
Semantic rich ICM algorithm for VHR satellite images segmentation. MVA 2015: 45-48 - [c2]Jérémie Sublime, Nistor Grozavu, Younès Bennani, Antoine Cornuéjols:
Vertical collaborative clustering using generative topographic maps. SoCPaR 2015: 199-204 - 2014
- [c1]Jérémie Sublime, Antoine Cornuéjols, Younès Bennani:
A New Energy Model for the Hidden Markov Random Fields. ICONIP (2) 2014: 60-67 - 2013
- [j1]Sonia Yassa, Jérémie Sublime, Rachid Chelouah, Hubert Kadima, GeunSik Jo, Bertrand Granado:
A genetic algorithm for multi-objective optimisation in workflow scheduling with hard constraints. Int. J. Metaheuristics 2(4): 415-433 (2013)
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last updated on 2024-11-07 20:34 CET by the dblp team
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