Spatiotemporal information fusion for human action recognition in videos. - Emmanuel Ramasso; Denis Pellerin; Costas Panagiotakis; Michèle Rombaut; George Tziritas; William Lim (EUSIPCO, 2005)

Shape-Motion Based Athlete Tracking for Multilevel Action Recognition. - Costas Panagiotakis; Emmanuel Ramasso; Georgios Tziritas; Michèle Rombaut; Denis Pellerin (AMDO, 2006)

Belief scheduling for recognition of human action sequence. - Emmanuel Ramasso; Denis Pellerin; Michèle Rombaut (FUSION, 2006)

A Temporal Belief Filter Improving Human Action Recognition in Videos. - Emmanuel Ramasso; Michèle Rombaut; Denis Pellerin (ICASSP (2), 2006)

Un filtre temporel crédibiliste pour la reconnaissance d'actions humaines dans les vidéos - Emmanuel Ramasso; Michèle Rombaut; Denis Pellerin (CoRR, 2006)

Automatic people detection and counting for athletic videos classification. - Costas Panagiotakis; Emmanuel Ramasso; Georgios Tziritas; Michèle Rombaut; Denis Pellerin (AVSS, 2007)

Forward-Backward-Viterbi Procedures in the Transferable Belief Model for State Sequence Analysis Using Belief Functions. - Emmanuel Ramasso; Michèle Rombaut; Denis Pellerin (ECSQARU, 2007)

State Filtering and Change Detection Using TBM Conflict Application to Human Action Recognition in Athletics Videos. - Emmanuel Ramasso; Michèle Rombaut; Denis Pellerin (IEEE Trans. Circuits Syst. Video Technol., 2007)

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). - Emmanuel Ramasso (2007)

Shape-Based Individual/Group Detection for Sport Videos Categorization. - Costas Panagiotakis; Emmanuel Ramasso; Georgios Tziritas; Michèle Rombaut; Denis Pellerin (Int. J. Pattern Recognit. Artif. Intell., 2008)

Quality evaluation of insulating parts by fusion of classifiers issued from tomographic images. - Lionel Valet; Emmanuel Ramasso; Sylvie Teyssier (Inf. Fusion, 2008)

Human action recognition in videos based on the Transferable Belief Model. - Emmanuel Ramasso; Costas Panagiotakis; Denis Pellerin; Michèle Rombaut (Pattern Anal. Appl., 2008)

Belief Scheduler based on model failure detection in the TBM framework. Application to human activity recognition. - Emmanuel Ramasso; Costas Panagiotakis; Michèle Rombaut; Denis Pellerin (Int. J. Approx. Reason., 2010)

Evidential Evolving Gustafson-Kessel Algorithm (E2GK) and its application to PRONOSTIA's data streams partitioning. - Lisa Serir; Emmanuel Ramasso; Patrick Nectoux; Olivier Bauer; Noureddine Zerhouni (CDC/ECC, 2011)

E2GK: Evidential Evolving Gustafsson-Kessel Algorithm for Data Streams Partitioning Using Belief Functions. - Lisa Serir; Emmanuel Ramasso; Noureddine Zerhouni (ECSQARU, 2011)

Parameter identification in Choquet Integral by the Kullback-Leibler divergence on continuous densities with application to classification fusion. - Emmanuel Ramasso; Sylvie Jullien (EUSFLAT Conf., 2011)

Partially-Hidden Markov Models. - Emmanuel Ramasso; Thierry Denoeux; Noureddine Zerhouni (Belief Functions, 2012)

Prognostic by Classification of Predictions Combining Similarity-Based Estimation and Belief Functions. - Emmanuel Ramasso; Michèle Rombaut; Noureddine Zerhouni (Belief Functions, 2012)

Evidential evolving Gustafson-Kessel algorithm for online data streams partitioning using belief function theory. - Lisa Serir; Emmanuel Ramasso; Noureddine Zerhouni (Int. J. Approx. Reason., 2012)

Segmentation and Sampling of Moving Object Trajectories Based on Representativeness. - Costas Panagiotakis; Nikos Pelekis; Ioannis Kopanakis; Emmanuel Ramasso; Yannis Theodoridis (IEEE Trans. Knowl. Data Eng., 2012)

Joint Prediction of Continuous and Discrete States in Time-Series Based on Belief Functions. - Emmanuel Ramasso; Michèle Rombaut; Noureddine Zerhouni (IEEE Trans. Cybern., 2013)

Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions. - Emmanuel Ramasso; Thierry Denoeux (IEEE Trans. Fuzzy Syst., 2014)

Remaining Useful Life Estimation by Classification of Predictions Based on a Neuro-Fuzzy System and Theory of Belief Functions. - Emmanuel Ramasso; Rafael Gouriveau (IEEE Trans. Reliab., 2014)

Weighted Maximum Likelihood for Parameters Learning Based on Noisy Labels in Discrete Hidden Markov Models. - Pablo Juesas Cano; Emmanuel Ramasso (ECSQARU, 2015)

Unsupervised Consensus Clustering of Acoustic Emission Time-Series for Robust Damage Sequence Estimation in Composites. - Emmanuel Ramasso; Vincent Placet; Mohamed Lamine Boubakar (IEEE Trans. Instrum. Meas., 2015)

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). - Emmanuel Ramasso (2016)

A Solution for the Learning Problem in Evidential (Partially) Hidden Markov Models Based on Conditional Belief Functions and EM. - Emmanuel Ramasso (IPMU (1), 2016)

Inference and Learning in Evidential Discrete Latent Markov Models. - Emmanuel Ramasso (IEEE Trans. Fuzzy Syst., 2017)

A Deep Reinforcement Learning Approach for Early Classification of Time Series. - Coralie Martinez; Guillaume Perrin; Emmanuel Ramasso; Michèle Rombaut (EUSIPCO, 2018)

Learning the representation of raw acoustic emission signals by direct generative modelling and its use in chronology-based clusters identification. - Emmanuel Ramasso; Pauline Butaud; Thomas Jeannin; Fabrizio Sarasini; Vincent Placet; Nathalie Godin; Jacopo Tirillò; Xavier Gabrion (Eng. Appl. Artif. Intell., 2020)

Adaptive early classification of temporal sequences using deep reinforcement learning. - Coralie Martinez; Emmanuel Ramasso; Guillaume Perrin; Michèle Rombaut (Knowl. Based Syst., 2020)

Autoregressive Hidden Markov Models with partial knowledge on latent space applied to aero-engines prognostics. - Pablo Juesas Cano; Emmanuel Ramasso; Sébastien Drujont; Vincent Placet (CoRR, 2021)

Clustering acoustic emission data streams with sequentially appearing clusters using mixture models. - Emmanuel Ramasso; Thierry Denoeux; Gaël Chevallier (CoRR, 2021)

CMUT-Based Sensor for Acoustic Emission Application: Experimental and Theoretical Contributions to Sensitivity Optimization. - Redha Boubenia; Patrice Le Moal; Gilles Bourbon; Emmanuel Ramasso; Eric Joseph (Sensors, 2021)

A Variational Bayesian Clustering Approach to Acoustic Emission Interpretation Including Soft Labels. - Martin Mbarga Nkogo; Emmanuel Ramasso; Patrice Le Moal; Gilles Bourbon (BELIEF, 2022)

Monitoring a Bolted Vibrating Structure Using Multiple Acoustic Emission Sensors: A Benchmark. - Emmanuel Ramasso; Benoît Verdin; Gaël Chevallier (Data, 2022)

Deep Evidential Clustering of Images. - Loïc Guiziou; Emmanuel Ramasso; Sébastien Thibaud; Sébastien Denneulin (BELIEF, 2024)

On the Condition Monitoring of Bolted Joints through Acoustic Emission and Deep Transfer Learning: Generalization, Ordinal Loss and Super-Convergence. - Emmanuel Ramasso; Rafael de O. Teloli; Romain Marcel (CoRR, 2024)

DEEM: A novel approach to semi-supervised and unsupervised image clustering under uncertainty using belief functions and convolutional neural networks. - Loïc Guiziou; Emmanuel Ramasso; Sébastien Thibaud; Sébastien Denneulin (Int. J. Approx. Reason., 2025)

A new criterion based on the distribution of cluster onsets for interpreting acoustic emission data signals: three case studies in structural and process monitoring. - Emmanuel Ramasso; Martin Mbarga Nkogo; Neha Chandarana; Gilles Bourbon; Patrice Le Moal; Quentin Lefèbvre; Martial Personeni; Constantinos Soutis; Matthieu Gresil; Sébastien Thibaud (Pattern Anal. Appl., 2025)