2 citations · 3 across the 7 of their papers we have counts for
7 papers
HASTE: A Platform for Rapid Post-Disaster Building Damage Assessment
Caleb Robinson, Anthony Ortiz, Simone Fobi Nsutezo +8
When a large disaster strikes, responders need a map of which buildings are damaged within hours. The models that do well on public benchmarks assume matched before-and-after image…
Core-Set Selection for Data-efficient Land Cover Segmentation
Keiller Nogueira, Akram Zaytar, Wanli Ma +9
The increasing accessibility of remotely sensed data and their potential to support large-scale decision-making have driven the development of deep learning models for many Earth O…
FLAVARS: A Multimodal Foundational Language and Vision Alignment Model for Remote Sensing
Isaac Corley, Simone Fobi Nsutezo, Anthony Ortiz +4
Remote sensing imagery is dense with objects and contextual visual information. There is a recent trend to combine paired satellite images and text captions for pretraining perform…
PGRID: Power Grid Reconstruction in Informal Developments Using High-Resolution Aerial Imagery
Simone Fobi Nsutezo, Amrita Gupta, Duncan Kebut +5
As of 2023, a record 117 million people have been displaced worldwide, more than double the number from a decade ago [22]. Of these, 32 million are refugees under the UNHCR mandate…
Mapping Global Floods with 10 Years of Satellite Radar Data
Amit Misra, Kevin White, Simone Fobi Nsutezo +2
Floods cause extensive global damage annually, making effective monitoring essential. While satellite observations have proven invaluable for flood detection and tracking, comprehe…
Rapid building damage assessment workflow: An implementation for the 2023 Rolling Fork, Mississippi tornado event
Caleb Robinson, Simone Fobi Nsutezo, Anthony Ortiz +7
Rapid and accurate building damage assessments from high-resolution satellite imagery following a natural disaster is essential to inform and optimize first responder efforts. Howe…
Mask Conditional Synthetic Satellite Imagery
Van Anh Le, Varshini Reddy, Zixi Chen +5
In this paper we propose a mask-conditional synthetic image generation model for creating synthetic satellite imagery datasets. Given a dataset of real high-resolution images and a…