activity
20172026
most citedDeep learning in remote sensing: a review

3.2k citations · 5.7k across the 43 of their papers we have counts for

collaborators
Showing cs.LGShow all

9 papers · 1 filter

cs.LG2025

Observation-driven correction of numerical weather prediction for marine winds

Matteo Peduto, Qidong Yang, Jonathan Giezendanner +2

Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observations over the ocean are sparse, h…

cs.LG2025

CISO: Species Distribution Modeling Conditioned on Incomplete Species Observations

Hager Radi Abdelwahed, Mélisande Teng, Robin Zbinden +4

Species distribution models (SDMs) are widely used to predict species' geographic distributions, serving as critical tools for ecological research and conservation planning. Typica…

cs.LG2025

MaskSDM with Shapley values to improve flexibility, robustness, and explainability in species distribution modeling

Robin Zbinden, Nina van Tiel, Gencer Sumbul +3

Species Distribution Models (SDMs) play a vital role in biodiversity research, conservation planning, and ecological niche modeling by predicting species distributions based on env…

cs.LG2024

Multi-Scale and Multimodal Species Distribution Modeling

Nina van Tiel, Robin Zbinden, Emanuele Dalsasso +3

Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs…

cs.LG2024

What to align in multimodal contrastive learning?

Benoit Dufumier, Javiera Castillo-Navarro, Devis Tuia +1

Humans perceive the world through multisensory integration, blending the information of different modalities to adapt their behavior. Contrastive learning offers an appealing solut…

cs.LG2024

Imbalance-aware Presence-only Loss Function for Species Distribution Modeling

Robin Zbinden, Nina van Tiel, Marc Rußwurm +1

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting e…