SAR2SAR: a self-supervised despeckling algorithm for SAR images. - Emanuele Dalsasso; Loïc Denis; Florence Tupin (CoRR, 2020)

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 001 (Remote. Sens., 2020)

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)

A Review of Deep-Learning Techniques for SAR Image Restoration. - Loïc Denis; Emanuele Dalsasso; Florence Tupin (IGARSS, 2021)

Despeckling Sentinel-1 GRD Images by Deep-Learning and Application to Narrow River Segmentation. - Nicolas Gasnier; Emanuele Dalsasso; Loïc Denis; Florence Tupin (IGARSS, 2021)

SAR2SAR: A Semi-Supervised Despeckling Algorithm for SAR Images. - Emanuele Dalsasso; Loïc Denis; Florence Tupin (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021)

Fast Strategies for Multi-Temporal Speckle Reduction of Sentinel-1 GRD Images. - Inès Meraoumia; Emanuele Dalsasso; Loïc Denis; Florence Tupin (IGARSS, 2022)

Multi-temporal speckle reduction with self-supervised deep neural networks. - Inès Meraoumia; Emanuele Dalsasso; Loïc Denis; Rémy Abergel; Florence Tupin (CoRR, 2022)

As If by Magic: Self-Supervised Training of Deep Despeckling Networks With MERLIN. - Emanuele Dalsasso; Loïc Denis; Florence Tupin (IEEE Trans. Geosci. Remote. Sens., 2022)

Deep learning for SAR imagery: from denoising to scene understanding. (Apprentissage profond pour l'imagerie SAR: du débruitage à l'interprétation de scène). - Emanuele Dalsasso (2022)

Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks. - Denis Coquenet; Clément Rambour; Emanuele Dalsasso; Nicolas Thome (CoRR, 2023)

Multitemporal Speckle Reduction With Self-Supervised Deep Neural Networks. - Inès Meraoumia; Emanuele Dalsasso; Loïc Denis; Rémy Abergel; Florence Tupin (IEEE Trans. Geosci. Remote. Sens., 2023)

POLO - Point-Based, Multi-class Animal Detection. - Giacomo May; Emanuele Dalsasso; Benjamin Kellenberger; Devis Tuia (ECCV Workshops (2), 2024)

Multi-scale and Multimodal Species Distribution Modeling. - Nina Van Tiel; Robin Zbinden; Emanuele Dalsasso; Benjamin Kellenberger; Loïc Pellissier; Devis Tuia (ECCV Workshops (2), 2024)

Self-Supervised Learning of Multi-Modal Cooperation for SAR Despeckling. - Victor Gaya; Emanuele Dalsasso; Loïc Denis; Florence Tupin; Béatrice Pinel-Puysségur; Cyrielle Guérin (IGARSS, 2024)

Just Project! Multi-Channel Despeckling, the Easy Way. - Loïc Denis; Emanuele Dalsasso; Florence Tupin (CoRR, 2024)

MERLIN-Seg: Self-supervised despeckling for label-efficient semantic segmentation. - Emanuele Dalsasso; Clément Rambour; Nicolas Trouvé; Nicolas Thome (Comput. Vis. Image Underst., 2024)

Self-supervised Change Detection via Cooperative Learning: A Two-Player Model. - Manon Béchaz; Emanuele Dalsasso; Ciprian Tomoiaga; Marcin Detyniecki; Devis Tuia (JURSE, 2025)

Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation. - Hugo Porta; Emanuele Dalsasso; Diego Marcos; Devis Tuia (WACV, 2025)

Just Project! Multichannel Despeckling, the Easy Way. - Loïc Denis; Emanuele Dalsasso; Florence Tupin (IEEE Trans. Geosci. Remote. Sens., 2025)

CanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities. - Hugo Porta; Emanuele Dalsasso; Jessica L. McCarty; Devis Tuia (CoRR, 2025)

SMARTIES: Spectrum-Aware Multi-Sensor Auto-Encoder for Remote Sensing Images. - Gencer Sumbul; Chang Xu; Emanuele Dalsasso; Devis Tuia (CoRR, 2025)