Large scale Post disaster damage assessment using AI and Remote Sensing
reference
- Deep Learning for Post-Hurricane Aerial Damage Assessment of Buildings. Computer‐Aided Civil and Infrastructure Engineering. 36(6), 695-710. https://doi.org/10.1111/mice.12658
- Drone Mapping of Damage Information in GPS-Denied Disaster Sites. Advanced Engineering Informatics. 51, 101450. https://doi.org/10.1016/j.aei.2021.101450
- Uncertainty-aware convolutional neural network for explainable AI-assisted disaster damage assessment. Structural Control and Health Monitoring. https://doi.org/10.1002/stc.3019
- Post-disaster damage classification based on deep multi-view image fusion. Computer‐Aided Civil and Infrastructure Engineering. (accepted will be published soon!)
- Bayesian Inference for Uncertainty-aware Post-disaster Damage Assessment using Artificial Intelligence. ASCE 2021 International Conference on Computing in Civil Engineering (I3CE 2021). DOI: https://doi.org/10.1061/9780784483893.020
- DoriaNET: A Visual Dataset from Hurricane Dorian for Post-disaster Building Damage Assessment. DesignSafe-CI. DOI: https://doi.org/10.17603/ds2-gqvg-qx37
- Convolutional neural networks for object detection in aerial imagery for disaster response and recovery. Advanced Engineering Informatics, 43, 101009. https://doi.org/10.1016/j.aei.2019.101009
- An uncertainty-aware framework for reliable disaster damage assessment via crowdsourcing. International Journal of Disaster Risk Reduction, 55, 102110. https://doi.org/10.1016/j.ijdrr.2021.102110
