Sylvain Chabanet
Publications
Publications
|
|
Toward an incremental Anderson-Darling algorithm for drift detection on cable-driven robotsMECATRONICS-REM 2025, Dec 2025, Paris, France |
|
|
CoreSelect: a new approach to select landmarks for dissimilarity space embedding15th International Joint Conference on Computational Intelligence, IJCCI 2023, International Conference on Neural Computation Theory and Applications, NCTA 2023, Nov 2023, Rome, Italy |
|
|
An object-oriented architecture to couple simulators and their machine learning surrogates models in the context of digital shadows22nd IFAC World Congress, IFAC 2023, Jul 2023, Yokohama, Japan. ⟨10.1016/j.ifacol.2023.10.1051⟩ |
|
|
Toward a self-adaptive digital twin based active learning method: an application to the lumber industry14th IFAC Workshop on Intelligent Manufacturins Systems, IMS 2022, Mar 2022, Tel Aviv, Israel |
|
|
A comparison of wood log dissimilarities to predict sawmill output with k-Nearest Neighbor algorithms4th International Conference on Advances in Signal Processing and Artificial Intelligence, ASPAI' 2022, Oct 2022, Corfu, Greece |
|
|
Toward a sawmill digital shadow based on coupled simulation and supervised learning models12th International Workshop on Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future, SOHOMA’22, Sep 2022, Bucharest, Romania |
|
|
Medoid-based MLP: an application to wood sawing simulator metamodeling13th International Conference on Neural Computation Theory and Applications, NCTA 2021, Oct 2021, Online streaming, Portugal |
|
|
A kNN approach based on ICP metrics for 3D scans matching: an application to the sawing process17th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2021, Jun 2021, Budapest (virtual), Hungary |
|
|
Dissimilarity to class medoids as features for 3D point cloud classificationIFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.573-581, ⟨10.1007/978-3-030-85906-0_62⟩ |
Active learning confidence measures for coupling strategies in digital twins integrating simulation and data-driven submodelsSimulation Modelling Practice and Theory, 2025, 140, pp.103092. ⟨10.1016/j.simpat.2025.103092⟩ |
|
MLP based on dissimilarity features: An application to wood sawing simulator metamodelingSN Computer Science, 2023, 4 (4), pp.408. ⟨10.1007/s42979-023-01852-8⟩ |
|
|
|
Toward digital twins for sawmill production planning and control: Benefits, opportunities, and challengesInternational Journal of Production Research, 2023, 61 (7), pp.2190-2213. ⟨10.1080/00207543.2022.2068086⟩ |
|
|
Coupling digital simulation and machine learning metamodel through an active learning approach in Industry4.0 contextComputers in Industry, 2021, 133, pp.103529. ⟨10.1016/j.compind.2021.103529⟩ |
|
|
Contributions aux ombres et jumeaux numériques dans l’industrie : proposition d’une stratégie de couplage entre modèles de simulation et d’apprentissage automatique appliquée aux scieriesAutomatique / Robotique. Université de Lorraine, 2023. Français. ⟨NNT : 2023LORR0131⟩ |