Filtering Internal tides from wide-swath altimeter data using Convolutional Neural Networks.

Redouane Lguensat; Ronan Fablet; Julien Le Sommer; Sammy Metref; Emmanuel Cosme; Kaouther Ouenniche; Lucas Drumetz; Jonathan Gula

doi:10.1109/IGARSS39084.2020.9323531

Conference papers

Filtering Internal tides from wide-swath altimeter data using Convolutional Neural Networks.

Redouane Lguensat ¹ Ronan Fablet ^{2, 3} Julien Le Sommer ¹ Sammy Metref ¹ Emmanuel Cosme ¹ Kaouther Ouenniche ³ Lucas Drumetz ³ Jonathan Gula ⁴

1 UNIVERSITE GRENOBLE ALPES CNRS IRD GRENOBLE INP UMR IGE FRA

2 Lab-STICC_IMTA_CID_TOMS

Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance

3 IMT Atlantique - SC - Département Signal et Communications

4 IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer

Document type :

Conference papers

Domain :

Sciences of the Universe [physics] / Ocean, Atmosphere

Computer Science [cs] / Machine Learning [cs.LG]

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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02941320
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Submitted on : Wednesday, September 16, 2020 - 11:02:55 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM

Filtering Internal tides from wide-swath altimeter data using Convolutional Neural Networks.

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Filtering Internal tides from wide-swath altimeter data using Convolutional Neural Networks.

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