PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts
January 29, 2020 Β· Declared Dead Β· π AAAI Conference on Artificial Intelligence
"No code URL or promise found in abstract"
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Authors
Tomaz Logar, Joseph Bullock, Edoardo Nemni, Lars Bromley, John A. Quinn, Miguel Luengo-Oroz
arXiv ID
2001.10685
Category
cs.CV: Computer Vision
Cross-listed
cs.HC,
cs.LG,
eess.IV
Citations
24
Venue
AAAI Conference on Artificial Intelligence
Last Checked
5 months ago
Abstract
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 be done accurately and in a timely manner to provide operational support. We present PulseSatellite, a collaborative satellite image analysis tool which leverages neural network models that can be retrained on-the fly and adapted to specific humanitarian contexts and geographies. We present two case studies, in mapping shelters and floods respectively, that illustrate the capabilities of PulseSatellite.
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