Detecting small objects over large areas remains a significant challenge in satellite imagery analytics. We propose a pipeline (SIMRDWN) that evaluates satellite images of arbitrarily large size at native resolution at a rate of > 0.2 km2/s.
The SpaceNet 4: Off-nadir building detection challenge has begun, and participants are vying for $50,000 of prize money by competing to see who can most accurately identify buildings in 27 different WorldView 2 satellite image collects taken at different angles over Atlanta.
Rapid detection of small objects over large areas remains one of the principal drivers of interest in satellite imagery analytics. This blog introduces the Satellite Imagery Multiscale Rapid Detection with Windowed Networks (SIMRDWN) framework.
SpaceNet is proud to release the Off-Nadir Imagery dataset, specifically built to explore advanced algorithms capabilities to process high off-nadir imagery. The dataset includes 27 WorldView 2 Satellite images from 7 degrees to 54 degrees off-nadir all captured within five minutes of each other.
Exploring how well one of the open source tools developed by CosmiQ Works (YOLT) performs on areas of interest in Tanzania.
Read how we developed a unique data-fusion mapping approach and the first independent remote sensing assessment of the recovery of electricity and infrastructure in Puerto Rico.