21 citations · 40 across the 20 of their papers we have counts for
6 papers · 1 filter
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…
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…
Hide and Seek: Investigating Redundancy in Earth Observation Imagery
Tasos Papazafeiropoulos, Nikolaos Ioannis Bountos, Nikolas Papadopoulos +1
The growing availability of Earth Observation (EO) data and recent advances in Computer Vision have driven rapid progress in machine learning for EO, producing domain-specific mode…
Magnifying change: Rapid burn scar mapping with multi-resolution, multi-source satellite imagery
Maria Sdraka, Dimitrios Michail, Ioannis Papoutsis
Delineating wildfire affected areas using satellite imagery remains challenging due to irregular and spatially heterogeneous spectral changes across the electromagnetic spectrum. W…