RasterNet: Modeling Free-Flow Speed using LiDAR and Overhead Imagery
Armin Hadzic, Hunter Blanton, Weilian Song, Mei Chen, Scott Workman, and Nathan Jacobs. EARTHVISION 2020
![RasterNet_pic](http://www.arminhadzic.com/images/EARTHVISION_RasterNet_teaser.gif)
We propose RasterNet, a multi-modal neural network architecture that combines overhead imagery and airborne LiDAR point clouds for the task of free-flow speed estimation.
Estimation Displaced Populations from Overhead
Armin Hadzic, Gordon Christie, Jeffrey Freeman, Amber Dismer, Stevan Bullard, Ashley Greiner, Nathan Jacobs, and Ryan Mukherjee. IGARSS 2020
![DCA_pic](http://www.arminhadzic.com/images/IGARSS_DCA_teaser.png)
We developed a method for estimating displaced community populations from high resolution overhead imagery.
FARSA: Fully Automated Roadway Safety Assessment
Weilian Song, Scott Workman, Armin Hadzic, Xu Zhang, Eric Green, Mei Chen, Reginald Souleyrette, and Nathan Jacobs. WACV 2018
![FARSA_pic](http://www.arminhadzic.com/images/FARSA_network_diagram.png)
We propose an automated process to access roadway safety using a deep convolutional neural network. Given a road segment and its street-level panorama, we can estimates a safety rating alongside many other road-level attributes, including curvature, roadside hazards, etc.