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Sylvain Chevallier
Professeur au LISN-CNRS, Université Paris-Saclay
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Libre accès
7
Documents
Affiliations actuelles
- 1066529
- 1061259
Identifiants chercheurs
- sylvain-chevallier
- Arxiv : chevallier_s_1
- IdRef : 142286826
- 0000-0003-3027-8241
- Google Scholar : https://scholar.google.fr/citations?user=j5Tu_SQAAAAJ&hl=fr
- ResearcherId : AAB-7621-2020
- ResearcherId : http://www.researcherid.com/rid/AAB-7621-2020
Présentation
After a PhD on bio-inspired robotic vision at LIMSI CNRS, I was a post-doc fellow in the neurocybernetic team of ETIS. I embraced a more machine learning centric approach to analyse EEG for Brain-Computer Interface (BCI) during two post-doc, one at INRIA and one at Telecom ParisTech. I worked as assistant professor at LISV, Université de Versailles-St Quentin on BCI for rehabilitation robotics, using Riemannian geometry and time series analysis. I am now full professor in A&O team of LISN-CNRS, Université Paris-Saclay.
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Online SSVEP-based BCI using Riemannian geometryNeurocomputing, 2016, 191, pp.55-68. ⟨10.1016/j.neucom.2016.01.007⟩
Article dans une revue
hal-01351623v1
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Ensemble learning based on functional connectivity and Riemannian geometry for robust workload estimationNeuroergonomics conference 2021, Sep 2021, Virtual event, Germany
Communication dans un congrès
hal-03359257v1
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From Euclidean to Riemannian Means: Information Geometry for SSVEP ClassificationGeometric Science of Information, Oct 2015, Palaiseau, France. pp.595-604, ⟨10.1007/978-3-319-25040-3_64⟩
Communication dans un congrès
hal-01351753v1
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On the need for metrics in dictionary learning assessment22nd European Signal Processing Conference (EUSIPCO) , Sep 2014, Lisbon, Portugal
Communication dans un congrès
hal-01352054v1
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Subspace metrics for multivariate dictionaries and application to EEGIEEE International Conference on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. ⟨10.1109/ICASSP.2014.6854993⟩
Communication dans un congrès
hal-01352047v1
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Riemannian classification for SSVEP based BCI: offline versus online implementationsBrain–Computer Interfaces Handbook: Technological and Theoretical Advances, 2018
Chapitre d'ouvrage
hal-01710089v1
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Using Riemannian geometry for SSVEP-based Brain Computer Interface[Research Report] Université de Versailles Saint-Quentin; Mensia Technologies, SA. 2015
Rapport
hal-01351685v1
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