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VeGAN - Predictive Vegetation Mapping
Generative AI - 2023
Seattle, WA
As an R&D project, I explored the use of Conditional Generational Adversarial Networks (cGANs) to predict the placement of foliage from an input heightmap. Using python, I generated a dataset of procedural sketch, elevation, vegetation map groups, then trained a modified Pix2Pix model to generate output vegetation maps from a user-supplied sketch or input heightmap.
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