no code implementations • 18 May 2020 • Christopher X. Ren, Amanda Ziemann, James Theiler, Alice M. S. Durieux
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 setting.
no code implementations • 28 Nov 2019 • Christopher X. Ren, Amanda Ziemann, Alice M. S. Durieux, James Theiler
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.
no code implementations • 5 Apr 2018 • James Theiler, Beate Zimmer, Amanda Ziemann
The generalized likelihood ratio test (GLRT) is used to derive a detector for solid sub-pixel targets in hyperspectral imagery.