4 papers
Deep Snow: Synthesizing Remote Sensing Imagery with Generative Adversarial Nets
Christopher X. Ren, Amanda Ziemann, James Theiler +1
In this work we demonstrate that generative adversarial networks (GANs) can be used to generate realistic pervasive changes in remote sensing imagery, even in an unpaired training…
On the Detectability of Conflict: a Remote Sensing Study of the Rohingya Conflict
Christopher X. Ren, Matthew T. Calef, Alice M. S. Durieux +2
The detection and quantification of conflict through remote sensing modalities represents a challenging but crucial aspect of human rights monitoring. In this work we demonstrate h…
BUDD: Multi-modal Bayesian Updating Deforestation Detections
Alice M. S Durieux, Christopher X. Ren, Matthew T. Calef +2
The global phenomenon of forest degradation is a pressing issue with severe implications for climate stability and biodiversity protection. In this work we generate Bayesian updati…
Cycle-Consistent Adversarial Networks for Realistic Pervasive Change Generation in Remote Sensing Imagery
Christopher X. Ren, Amanda Ziemann, Alice M. S. Durieux +1
This paper introduces a new method of generating realistic pervasive changes in the context of evaluating the effectiveness of change detection algorithms in controlled settings. T…