Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage

Autor: Evangelos Moschos, Alexandre Stegner, Olivier Schwander, Patrick Gallinari

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 3437-3447 (2020)

Mesoscale oceanic eddies have a visible signature on sea surface temperature (SST) satellite images, portraying diverse patterns of coherent vortices, temperature gradients, and swirling filaments. However, learning the regularities of such signature

Externí odkaz: https://doaj.org/article/199cf8c9a2914a329b68bcced4bd6581

Real-Time Validation of Operational Ocean Models Via Eddy-Decting Deep Neural Networks

Autor: Evangelos Moschos, Alexandre Stegner, Briac Le Vu, Olivier Schwander

Publikováno v: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::90ab56350d7be1fa140bbb51748e73c4
https://doi.org/10.1109/igarss46834.2022.9883253

Deep Learning and Information Geometry for Drone Micro-Doppler Radar Classification

Autor: Jean Yves Schneider, Daniel A. Brooks, Frederic Barbaresco, Matthieu Cord, Olivier Schwander

Publikováno v: 2020 IEEE Radar Conference (RadarConf20).

In this work, we build dedicated learning models for micro-Doppler radar time series classification. We develop both deep temporal architectures based on time-frequency representations, and also directly study the signal's underlying statistical Gaus

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cadec61fdc76ecf335cc1f606a7ffc93
https://doi.org/10.1109/radarconf2043947.2020.9266689

Reduced Basis’ Acquisition by a Learning Process for Rapid On-line Approximation of Solution to PDE’s: Laminar Flow Past a Backstep

Autor: Olivier Schwander, Tommaso Taddei, Maxime Sangnier, Patrick Gallinari, Yvon Maday

Publikováno v: Archives of Computational Methods in Engineering. 25:131-141

Reduced basis methods for the approximation to parameter-dependent partial differential equations are now well-developed and start to be used for industrial applications. The classical implementation of the reduced basis method goes through two stage

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::97a4c2996ef7bcc341bcb1713013ee08
https://doi.org/10.1007/s11831-017-9238-z

Second-order networks in PyTorch

Autor: Matthieu Cord, Daniel A. Brooks, Jean-Yves Schneider, Frederic Barbaresco, Olivier Schwander

Publikováno v: GSI 2019-4th International Conference on Geometric Science of Information
GSI 2019-4th International Conference on Geometric Science of Information, Aug 2019, Toulouse, France. pp.751-758, ⟨10.1007/978-3-030-26980-7_78⟩
Lecture Notes in Computer Science ISBN: 9783030269791
GSI

International audience; Classification of Symmetric Positive Definite (SPD) matrices is gaining momentum in a variety machine learning application fields. In this work we propose a Python library which implements neural networks on SPD matrices, base

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7b3a8e07c3436773b29ea5f7ff52794
https://hal.archives-ouvertes.fr/hal-02290841