Search Results for author:
Found 3 papers, 0 papers with code
FloodDamageCast: Building Flood Damage Nowcasting with Machine Learning and Data Augmentation
Near-real time estimation of damage to buildings and infrastructure, referred to as damage nowcasting in this study, is crucial for empowering emergency responders to make informed decisions regarding evacuation orders and infrastructure repair priorities during disaster response and recovery.
MaxFloodCast: Ensemble Machine Learning Model for Predicting Peak Inundation Depth And Decoding Influencing Features
Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events.
FairMobi-Net: A Fairness-aware Deep Learning Model for Urban Mobility Flow Generation
Generating realistic human flows across regions is essential for our understanding of urban structures and population activity patterns, enabling important applications in the fields of urban planning and management.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
