18 papers
On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing
Simon Lösche, Barış Büyüktaş, Mathis Adler +3
Federated learning (FL) enables collaborative training of deep learning models across decentralized image archives without requiring data centralization. This paradigm is particula…
Thalia: A Global, Multi-Modal Dataset for Volcanic Activity Monitoring
Nikolas Papadopoulos, Nikolaos Ioannis Bountos, Maria Sdraka +3
Monitoring volcanic activity is of paramount importance to safeguarding lives, infrastructure, and ecosystems. However, only a small fraction of known volcanoes are continuously mo…
Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Spyros Kondylatos, Nikolas Papadopoulos, Gustau Camps-Valls +1
Wildfires are among the most severe natural hazards, posing a significant threat to both humans and natural ecosystems. The growing risk of wildfires increases the demand for forec…
OSMGraphCLIP: Learning Global Location Representations from OpenStreetMap Graphs
Dimitrios Michail, Eleni Saka, Ioannis Giannopoulos +1
We present OSMGraphCLIP, a CLIP-style geospatial representation model that learns global location embeddings from freely available OpenStreetMap (OSM) data. OSMGraphCLIP represents…
Set Prediction for Next-Day Active Fire Forecasting
Yuchen Bai, Georgios Athanasiou, Xin Yu +4
Accurate next-day active fire forecasts can support early warning, disaster response, forest risk assessment, and downstream estimation of fire-related carbon emissions. Existing m…
BigEarthNet.txt: A Large-Scale Multi-Sensor Image-Text Dataset and Benchmark for Earth Observation
Johann-Ludwig Herzog, Mathis Jürgen Adler, Leonard Hackel +5
Vision-langugage models (VLMs) have shown strong performance in computer vision (CV), yet their performance on remote sensing (RS) data remains limited due to the lack of large-sca…