5 citations · 7 across the 6 of their papers we have counts for
6 papers
Conditional Progressive Generative Adversarial Network for satellite image generation
Renato Cardoso, Sofia Vallecorsa, Edoardo Nemni
Image generation and image completion are rapidly evolving fields, thanks to machine learning algorithms that are able to realistically replace missing pixels. However, generating…
SAR-based landslide classification pretraining leads to better segmentation
Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh +5
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affec…
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh +5
With climate change predicted to increase the likelihood of landslide events, there is a growing need for rapid landslide detection technologies that help inform emergency response…
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment
Hongruixuan Chen, Edoardo Nemni, Sofia Vallecorsa +3
Accurate and fine-grained information about the extent of damage to buildings is essential for humanitarian relief and disaster response. However, as the most commonly used archite…
Proceedings of NeurIPS 2020 Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
Ritwik Gupta, Eric T. Heim, Edoardo Nemni
These are the "proceedings" of the 2nd AI + HADR workshop which was held virtually on December 12, 2020 as part of the Neural Information Processing Systems conference. These are n…
PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts
Tomaz Logar, Joseph Bullock, Edoardo Nemni +3
Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis. In a humanitarian context, very specific satellite image analysis tasks must b…