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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 : Multi-task learning Length estimation Classification Index Terms-Deep neural network Sentinel-1 SAR images Ship detection
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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02285670
Contributor : Ronan Fablet <>
Submitted on : Wednesday, November 13, 2019 - 6:14:06 PM
Last modification on : Wednesday, August 5, 2020 - 3:42:08 AM

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  • HAL Id : hal-02285670, version 1

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UNIV-BREST | UR1-UFR-ISTIC | UNIV-RENNES | IMT-ATLANTIQUE | IRISA-D5 | CENTRALESUPELEC | CNRS | IRISA | UNIV-RENNES1 | INSTITUT-TELECOM | ENIB | LAB-STICC | INRIA | IRISA_UBS | UBS | INSA-RENNES

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Clément Dechesne, Sébastien Lefèvre, Rodolphe Vadaine, Guillaume Hajduch, Ronan Fablet. Multi-task deep learning from Sentinel-1 SAR: ship detection, classification and length estimation. BiDS'19 : Conference on Big Data from Space, Feb 2019, Munich, Germany. ⟨hal-02285670⟩

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