1 code implementation • CVPR 2021 • Adam Van Etten, Daniel Hogan, Jesus Martinez-Manso, Jacob Shermeyer, Nicholas Weir, Ryan Lewis
Each building is assigned a unique identifier (i. e. address), which permits tracking of individual objects over time.
no code implementations • 4 Jun 2020 • Jacob Shermeyer, Thomas Hossler, Adam Van Etten, Daniel Hogan, Ryan Lewis, Daeil Kim
RarePlanes is a unique open-source machine learning dataset that incorporates both real and synthetically generated satellite imagery.
3 code implementations • 14 Apr 2020 • Jacob Shermeyer, Daniel Hogan, Jason Brown, Adam Van Etten, Nicholas Weir, Fabio Pacifici, Ronny Haensch, Alexei Bastidas, Scott Soenen, Todd Bacastow, Ryan Lewis
The dataset and challenge focus on mapping and building footprint extraction using a combination of these data sources.
no code implementations • 16 Jan 2020 • Adam Van Etten, Jacob Shermeyer, Daniel Hogan, Nicholas Weir, Ryan Lewis
Identification of road networks and optimal routes directly from remote sensing is of critical importance to a broad array of humanitarian and commercial applications.
no code implementations • ICCV 2019 • Nicholas Weir, David Lindenbaum, Alexei Bastidas, Adam Van Etten, Sean McPherson, Jacob Shermeyer, Varun Kumar, Hanlin Tang
To address this problem, we present an open source Multi-View Overhead Imagery dataset, termed SpaceNet MVOI, with 27 unique looks from a broad range of viewing angles (-32. 5 degrees to 54. 0 degrees).
2 code implementations • 10 Dec 2018 • Jacob Shermeyer, Adam Van Etten
We also quantify the performance of object detection as a function of native resolution and object pixel size.
no code implementations • 16 Jul 2018 • Jacob Shermeyer
Based upon our approach we can identify and evaluate: 1) the recovery of electrical power compared to pre-storm levels, 2) the location of potentially damaged infrastructure that has yet to recover from the storm, and 3) the number of persons without power over time.