A case study from ResearchGate
We present a project that aims to generate images that depict accurate, vivid, and personalized outcomes of climate change using Cycle-Consistent Adversarial Networks (CycleGANs).
Case Study: Explores the potential of using images from a simulated 3D environment to improve a domain adaptation task carried out by the MUNIT architecture, aiming to use the resulting images to raise awareness of the potential future impacts of climate change. The case study aims to develop an interactive website that, given a user-entered address, will display a plausible Google StreetView image of its climate future based on the climate prediction models.
