8 citations · 11 across the 3 of their papers we have counts for
4 papers
Street to Cloud: Improving Flood Maps With Crowdsourcing and Semantic Segmentation
Veda Sunkara, Matthew Purri, Bertrand Le Saux +1
To address the mounting destruction caused by floods in climate-vulnerable regions, we propose Street to Cloud, a machine learning pipeline for incorporating crowdsourced ground tr…
H2O-Net: Self-Supervised Flood Segmentation via Adversarial Domain Adaptation and Label Refinement
Peri Akiva, Matthew Purri, Kristin Dana +2
Accurate flood detection in near real time via high resolution, high latency satellite imagery is essential to prevent loss of lives by providing quick and actionable information.…
Angular Luminance for Material Segmentation
Jia Xue, Matthew Purri, Kristin Dana
Moving cameras provide multiple intensity measurements per pixel, yet often semantic segmentation, material recognition, and object recognition do not utilize this information. Wit…
Material Segmentation of Multi-View Satellite Imagery
Matthew Purri, Jia Xue, Kristin Dana +5
Material recognition methods use image context and local cues for pixel-wise classification. In many cases only a single image is available to make a material prediction. Image seq…