Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox

Picture for Florence Tupin

Florence Tupin

LTCI, Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France

unrolling palm for sparse semi-blind source separation



Mohammad Fahes , Christophe Kervazo , Jérôme Bobin , Florence Tupin


   Access Paper or Ask Questions

As if by magic: self-supervised training of deep despeckling networks with MERLIN



Emanuele Dalsasso , Loïc Denis , Florence Tupin

* To appear on IEEE Transactions on Geoscience and Remote Sensing 

   Access Paper or Ask Questions

Multi-View Radar Semantic Segmentation



Arthur Ouaknine , Alasdair Newson , Patrick Pérez , Florence Tupin , Julien Rebut

* 15 pages, 8 figures. Preprint. Under review 

   Access Paper or Ask Questions

Urban Surface Reconstruction in SAR Tomography by Graph-Cuts



Clément Rambour , Loïc Denis , Florence Tupin , Hélène Oriot , Yue Huang , Laurent Ferro-Famil

* Computer Vision and Image Understanding 188 (2019) 102791 

   Access Paper or Ask Questions

Despeckling Sentinel-1 GRD images by deep learning and application to narrow river segmentation



Nicolas Gasnier , Emanuele Dalsasso , Loïc Denis , Florence Tupin


   Access Paper or Ask Questions

Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning



Emanuele Dalsasso , Inès Meraoumia , Loïc Denis , Florence Tupin


   Access Paper or Ask Questions

A review of deep-learning techniques for SAR image restoration



Loïc Denis , Emanuele Dalsasso , Florence Tupin


   Access Paper or Ask Questions

SAR2SAR: a self-supervised despeckling algorithm for SAR images



Emanuele Dalsasso , Loïc Denis , Florence Tupin

* Article submitted to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Code is made available at https://github.com/emanueledalsasso/SAR2SAR 

   Access Paper or Ask Questions

SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy



Emanuele Dalsasso , Xiangli Yang , Loïc Denis , Florence Tupin , Wen Yang

* Article submitted to Remote Sensing, MDPI. Notebook with Colab compatibility is available at https://github.com/emanueledalsasso/SAR-CNN 

   Access Paper or Ask Questions

1
2
>>