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

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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

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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

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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.