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ORCIDEmmanuel Ramasso
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2020 – today
- 2024
[c16]Loïc Guiziou, Emmanuel Ramasso, Sébastien Thibaud, Sébastien Denneulin:
Deep Evidential Clustering of Images. BELIEF 2024: 3-12- [i4]Emmanuel Ramasso, Rafael de O. Teloli, Romain Marcel:
On the Condition Monitoring of Bolted Joints through Acoustic Emission and Deep Transfer Learning: Generalization, Ordinal Loss and Super-Convergence. CoRR abs/2405.20887 (2024) - 2022
- [j16]Emmanuel Ramasso
, Benoît Verdin, Gaël Chevallier:
Monitoring a Bolted Vibrating Structure Using Multiple Acoustic Emission Sensors: A Benchmark. Data 7(3): 31 (2022) - [c15]Martin Mbarga Nkogo, Emmanuel Ramasso, Patrice Le Moal, Gilles Bourbon:
A Variational Bayesian Clustering Approach to Acoustic Emission Interpretation Including Soft Labels. BELIEF 2022: 23-32 - 2021
- [j15]Redha Boubenia, Patrice Le Moal, Gilles Bourbon, Emmanuel Ramasso, Eric Joseph:
CMUT-Based Sensor for Acoustic Emission Application: Experimental and Theoretical Contributions to Sensitivity Optimization. Sensors 21(6): 2042 (2021) - [i3]Pablo Juesas Cano, Emmanuel Ramasso, Sébastien Drujont, Vincent Placet:
Autoregressive Hidden Markov Models with partial knowledge on latent space applied to aero-engines prognostics. CoRR abs/2105.00211 (2021) - [i2]Emmanuel Ramasso, Thierry Denoeux, Gaël Chevallier:
Clustering acoustic emission data streams with sequentially appearing clusters using mixture models. CoRR abs/2108.11211 (2021) - 2020
- [j14]Emmanuel Ramasso, Pauline Butaud, Thomas Jeannin, Fabrizio Sarasini, Vincent Placet, Nathalie Godin, Jacopo Tirillò, Xavier Gabrion:
Learning the representation of raw acoustic emission signals by direct generative modelling and its use in chronology-based clusters identification. Eng. Appl. Artif. Intell. 90: 103478 (2020) - [j13]Coralie Martinez, Emmanuel Ramasso, Guillaume Perrin, Michèle Rombaut:
Adaptive early classification of temporal sequences using deep reinforcement learning. Knowl. Based Syst. 190: 105290 (2020)
2010 – 2019
- 2018
- [c14]Coralie Martinez, Guillaume Perrin, Emmanuel Ramasso, Michèle Rombaut:
A Deep Reinforcement Learning Approach for Early Classification of Time Series. EUSIPCO 2018: 2030-2034 - 2017
- [j12]Emmanuel Ramasso:
Inference and Learning in Evidential Discrete Latent Markov Models. IEEE Trans. Fuzzy Syst. 25(5): 1102-1114 (2017) - 2016
- [b2]Emmanuel Ramasso:
Méthodologies d'analyse de séries temporelles sous incertitudes aléatoires et épistémiques pour le suivi et le pronostic de l'état de systèmes et structures - De l'estimation d'une cinétique d'endommagement à son contrôle. (Methodologies for time series analysis under aleatoric and epistemic uncertainties for structural health monitoring and prognostics). University of Franche-Comté, France, 2016 - [c13]Emmanuel Ramasso:
A Solution for the Learning Problem in Evidential (Partially) Hidden Markov Models Based on Conditional Belief Functions and EM. IPMU (1) 2016: 299-310 - 2015
- [j11]Emmanuel Ramasso, Vincent Placet, Mohamed Lamine Boubakar:
Unsupervised Consensus Clustering of Acoustic Emission Time-Series for Robust Damage Sequence Estimation in Composites. IEEE Trans. Instrum. Meas. 64(12): 3297-3307 (2015) - [c12]Pablo Juesas Cano, Emmanuel Ramasso:
Weighted Maximum Likelihood for Parameters Learning Based on Noisy Labels in Discrete Hidden Markov Models. ECSQARU 2015: 451-460 - 2014
- [j10]Emmanuel Ramasso, Thierry Denoeux:
Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions. IEEE Trans. Fuzzy Syst. 22(2): 395-405 (2014) - [j9]Emmanuel Ramasso, Rafael Gouriveau:
Remaining Useful Life Estimation by Classification of Predictions Based on a Neuro-Fuzzy System and Theory of Belief Functions. IEEE Trans. Reliab. 63(2): 555-566 (2014) - 2013
- [j8]Emmanuel Ramasso, Michèle Rombaut, Noureddine Zerhouni:
Joint Prediction of Continuous and Discrete States in Time-Series Based on Belief Functions. IEEE Trans. Cybern. 43(1): 37-50 (2013) - 2012
- [j7]Lisa Serir, Emmanuel Ramasso, Noureddine Zerhouni:
Evidential evolving Gustafson-Kessel algorithm for online data streams partitioning using belief function theory. Int. J. Approx. Reason. 53(5): 747-768 (2012) - [j6]Costas Panagiotakis, Nikos Pelekis, Ioannis Kopanakis, Emmanuel Ramasso, Yannis Theodoridis:
Segmentation and Sampling of Moving Object Trajectories Based on Representativeness. IEEE Trans. Knowl. Data Eng. 24(7): 1328-1343 (2012) - [c11]Emmanuel Ramasso, Michèle Rombaut, Noureddine Zerhouni:
Prognostic by Classification of Predictions Combining Similarity-Based Estimation and Belief Functions. Belief Functions 2012: 61-68 - [c10]Emmanuel Ramasso, Thierry Denoeux, Noureddine Zerhouni:
Partially-Hidden Markov Models. Belief Functions 2012: 359-366 - 2011
- [c9]Lisa Serir, Emmanuel Ramasso, Patrick Nectoux, Olivier Bauer, Noureddine Zerhouni:
Evidential Evolving Gustafson-Kessel Algorithm (E2GK) and its application to PRONOSTIA's data streams partitioning. CDC/ECC 2011: 8273-8278 - [c8]Lisa Serir, Emmanuel Ramasso, Noureddine Zerhouni:
E2GK: Evidential Evolving Gustafsson-Kessel Algorithm for Data Streams Partitioning Using Belief Functions. ECSQARU 2011: 326-337 - [c7]Emmanuel Ramasso, Sylvie Jullien:
Parameter identification in Choquet Integral by the Kullback-Leibler divergence on continuous densities with application to classification fusion. EUSFLAT Conf. 2011: 132-139 - 2010
- [j5]Emmanuel Ramasso, Costas Panagiotakis, Michèle Rombaut, Denis Pellerin:
Belief Scheduler based on model failure detection in the TBM framework. Application to human activity recognition. Int. J. Approx. Reason. 51(7): 846-865 (2010)
2000 – 2009
- 2008
- [j4]Costas Panagiotakis, Emmanuel Ramasso, Georgios Tziritas, Michèle Rombaut, Denis Pellerin:
Shape-Based Individual/Group Detection for Sport Videos Categorization. Int. J. Pattern Recognit. Artif. Intell. 22(6): 1187-1213 (2008) - [j3]Lionel Valet, Emmanuel Ramasso, Sylvie Teyssier:
Quality evaluation of insulating parts by fusion of classifiers issued from tomographic images. Inf. Fusion 9(2): 211-222 (2008) - [j2]Emmanuel Ramasso, Costas Panagiotakis, Denis Pellerin, Michèle Rombaut:
Human action recognition in videos based on the Transferable Belief Model. Pattern Anal. Appl. 11(1): 1-19 (2008) - 2007
- [b1]Emmanuel Ramasso:
Reconnaissance de séquences d'états par le Modèle des Croyances Transférables. Application à l'analyse de vidéos d'athlétisme. (State sequence recognition based on the Transferable Belief Model. Application to athletics videos analysis). Joseph Fourier University, Grenoble, France, 2007 - [j1]Emmanuel Ramasso, Michèle Rombaut, Denis Pellerin:
State Filtering and Change Detection Using TBM Conflict Application to Human Action Recognition in Athletics Videos. IEEE Trans. Circuits Syst. Video Technol. 17(7): 944-949 (2007) - [c6]Costas Panagiotakis, Emmanuel Ramasso, Georgios Tziritas, Michèle Rombaut, Denis Pellerin:
Automatic people detection and counting for athletic videos classification. AVSS 2007: 429-434 - [c5]Emmanuel Ramasso, Michèle Rombaut, Denis Pellerin:
Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions. ECSQARU 2007: 405-417 - 2006
- [c4]Costas Panagiotakis, Emmanuel Ramasso, Georgios Tziritas, Michèle Rombaut, Denis Pellerin:
Shape-Motion Based Athlete Tracking for Multilevel Action Recognition. AMDO 2006: 385-394 - [c3]Emmanuel Ramasso, Denis Pellerin, Michèle Rombaut:
Belief scheduling for recognition of human action sequence. FUSION 2006: 1-8 - [c2]Emmanuel Ramasso, Michèle Rombaut, Denis Pellerin:
A Temporal Belief Filter Improving Human Action Recognition in Videos. ICASSP (2) 2006: 141-144 - [i1]Emmanuel Ramasso, Michèle Rombaut, Denis Pellerin:
Un filtre temporel crédibiliste pour la reconnaissance d'actions humaines dans les vidéos. CoRR abs/cs/0607087 (2006) - 2005
- [c1]Emmanuel Ramasso, Denis Pellerin, Costas Panagiotakis, Michèle Rombaut, George Tziritas, William Lim:
Spatiotemporal information fusion for human action recognition in videos. EUSIPCO 2005: 1-4
Coauthor Index
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