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Found 7 papers, 2 papers with code
Conditional Progressive Generative Adversarial Network for satellite image generation
In this work, we formulate the image generation task as completion of an image where one out of three corners is missing.
Deep learning based landslide density estimation on SAR data for rapid response
Since such data might not be available during other events or regions, we aimed to produce a landslide density map using only elevation and SAR data to be useful to decision-makers in rapid response scenarios.
SAR-based landslide classification pretraining leads to better segmentation
In the case of landslides, rapid assessment involves determining the extent of the area affected and measuring the size and location of individual landslides.
Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes
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 responses.
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment
Considering the frontier advances of Transformer architecture in the computer vision field, in this paper, we present the first attempt at designing a Transformer-based damage assessment architecture (DamFormer).
Ranked #6 on
Extracting Buildings In Remote Sensing Images
on xBD
Disaster Response
Extracting Buildings In Remote Sensing Images
+1
Proceedings of NeurIPS 2020 Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
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.
PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts
Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis.
