35 citations · 41 across the 2 of their papers we have counts for
Showing 2018 · cs.CVShow all
2 papers · 2 filters
cs.CV2018★ 35 cited
Benchmark Dataset for Automatic Damaged Building Detection from Post-Hurricane Remotely Sensed Imagery
Sean Andrew Chen, Andrew Escay, Christopher Haberland +3
Rapid damage assessment is of crucial importance to emergency responders during hurricane events, however, the evaluation process is often slow, labor-intensive, costly, and error-…
cs.CV2018
Building Damage Annotation on Post-Hurricane Satellite Imagery Based on Convolutional Neural Networks
Quoc Dung Cao, Youngjun Choe
After a hurricane, damage assessment is critical to emergency managers for efficient response and resource allocation. One way to gauge the damage extent is to quantify the number…