Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation

Clément Dechesne; Sébastien Lefèvre; Rodolphe Vadaine; Guillaume Hajduch; Ronan Fablet

Conference papers

Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation

Clément Dechesne ^{1, 2} Sébastien Lefèvre ³ Rodolphe Vadaine ⁴ Guillaume Hajduch ⁴ Ronan Fablet ^{1, 2}

1 Lab-STICC_IMTA_CID_TOMS

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

2 IMT Atlantique - SC - Département Signal et Communications

3 OBELIX - Environment observation with complex imagery

UBS - Université de Bretagne Sud, IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE

4 CLS - Collecte Localisation Satellites (Entreprise)

Keywords : Index Terms-Deep neural network Sentinel-1 SAR images Classification Ship detection Length estimation Multi-task learning

Document type :

Conference papers

Domain :

Engineering Sciences [physics] / Signal and Image processing

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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02285670
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Submitted on : Wednesday, November 13, 2019 - 6:14:06 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM

Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation

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Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation

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