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Image Restoration for Remote Sensing: Overview and toolbox

 Behnood Rasti , Yi Chang , Emanuele Dalsasso , Loic Denis , Pedram Ghamisi
IEEE geoscience and remote sensing magazine, 2022, 10 (2), pp.201-230. ⟨10.1109/MGRS.2021.3121761⟩
Article dans une revue ujm-03842768v1
Image document

Self-supervised training strategies for SAR image despeckling with deep neural networks

 Emanuele Dalsasso , Loïc Denis , Max Muzeau , Florence Tupin
14th European Conference on Synthetic Aperture Radar (EUSAR), Jul 2022, Leipzig, Germany
Communication dans un congrès hal-03589245v2
Image document

A review of deep-learning techniques for SAR image restoration

 Loïc Denis , Emanuele Dalsasso , Florence Tupin
IGARSS 2021, Jul 2021, Bruxelles (virtual), Belgium
Communication dans un congrès ujm-03123042v1
Image document

How to handle spatial correlations in SAR despeckling? Resampling strategies and deep learning approaches

 Emanuele Dalsasso , Loïc Denis , Florence Tupin
EUSAR 2021: 13th European Conference on Synthetic Aperture Radar, Mar 2021, Leipzig (virtual), Germany. pp.1-6
Communication dans un congrès hal-02538046v2
Image document

Débruitage multi-temporel d'images radar à synthèse d'ouverture par apprentissage profond auto-supervisé

 Inès Meraoumia , Emanuele Dalsasso , Loïc Denis , Florence Tupin
GRETSI 2022, Sep 2022, Nancy, France
Communication dans un congrès hal-03806566v1

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

 Nicolas Gasnier , Emanuele Dalsasso , Loïc Denis , Florence Tupin
IGARSS 2021, Jul 2021, Bruxelles, Belgium
Communication dans un congrès hal-03129006v1
Image document

Self-supervised learning of deep despeckling networks with MERLIN: ensuring the statistical independence of the real and imaginary parts

 Emanuele Dalsasso , Frédéric Brigui , Loïc Denis , Rémy Abergel , Florence Tupin
2023
Pré-publication, Document de travail hal-04245667v1
Image document

Débruitage multi-modal d'images radar à synthèse d'ouverture par apprentissage profond auto-supervisé

 Victor Gaya , Emanuele Dalsasso , Loïc Denis , Florence Tupin , Béatrice Pinel-Puysségur , et al.
GRETSI, Aug 2023, Grenoble, France
Communication dans un congrès hal-04144686v1

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

 Emanuele Dalsasso , Inès Meraoumia , Loïc Denis , Florence Tupin
IGARSS 2021, Jul 2021, Bruxelles (virtual), Belgium
Communication dans un congrès hal-03129020v1
Image document

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

 Emanuele Dalsasso , Loïc Denis , Florence Tupin
IEEE Transactions on Geoscience and Remote Sensing, 2022, 60
Article dans une revue ujm-03270455v2

SAR2SAR: a semi-supervised despeckling algorithm for SAR images

 Emanuele Dalsasso , Loïc Denis , Florence Tupin
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, In press, pp.1-1. ⟨10.1109/JSTARS.2021.3071864⟩
Article dans une revue hal-03148450v1
Image document

Deep learning for SAR imagery : from denoising to scene understanding

 Emanuele Dalsasso
Artificial Intelligence [cs.AI]. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT008⟩
Thèse tel-03666646v1
Image document

DESPECKLING OF DUAL-POL GRD SENTINEL-1 IMAGES IN EXTRA-WIDE MODE BY DEEP LEARNING

 Inès Meraoumia , Ratha Debanshu , Emanuele Dalsasso , Loïc Denis , Florence Tupin , et al.
International Geoscience and Remote Sensing Symposium (IGARSS) 2023, Jul 2023, Pasadena (California), United States
Communication dans un congrès hal-04152906v1

Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks

 Denis Coquenet , Clément Rambour , Emanuele Dalsasso , Nicolas Thome
2023
Pré-publication, Document de travail hal-04162923v1
Image document

Learning a versatile representation of SAR data for regression and segmentation by leveraging self-supervised despeckling with MERLIN

 Emanuele Dalsasso , Clément Rambour , Loïc Denis , Florence Tupin
2023
Pré-publication, Document de travail hal-04245654v1
Image document

FAST STRATEGIES FOR MULTI-TEMPORAL SPECKLE REDUCTION OF SENTINEL-1 GRD IMAGES

 Inès Meraoumia , Emanuele Dalsasso , Loïc Denis , Florence Tupin
IGARSS, 2022, Kuala Lumpur, Malaysia
Communication dans un congrès hal-03756068v1
Image document

Apprentissage autosupervisé pour le despeckling d'images SAR avec MERLIN : application aux images Sentinel-1 Stripmap

 Emanuele Dalsasso , Loïc Denis , Florence Tupin
GRETSI 2022 (Groupe de Recherche et d'Etudes de Traitement du Signal et des Images), Sep 2022, Nancy, France
Communication dans un congrès hal-03781619v1

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
Remote Sensing, 2020, 12 (16), pp.2636. ⟨10.3390/rs12162636⟩
Article dans une revue hal-02944565v1
Image document

MERLIN-Seg: self-supervised despeckling for label-efficient semantic segmentation

 Emanuele Dalsasso , Clément Rambour , Nicolas Trouvé , Nicolas Thome
Computer Vision and Image Understanding, 2024, 241, ⟨10.1016/j.cviu.2024.103940⟩
Article dans une revue hal-04163624v2
Image document

Multi-temporal speckle reduction with self-supervised deep neural networks

 Inès Meraoumia , Emanuele Dalsasso , Loïc Denis , Rémy Abergel , Florence Tupin
IEEE Transactions on Geoscience and Remote Sensing, 2023, 61
Article dans une revue hal-03907022v1
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