This repository holds resources related to the Fresh Eyes Workshop, which presents tools and techniques for the application of Machine Learning (ML) to Generative Architectural Design (GAD).
The workshop is based on a modest modification of a 3-step process that is well-known in generative architectural design, and that proceeds as: generate, evaluate, iterate. In place of the typical approaches to the evaluation step of this cycle, here we employ an ML process: a Convolutional Neural Net (CNN) trained to perform image classification. Such an approach allows the integration of a variety of tacit and heretofore un-encapsulatable design criteria - such as architectural style, spatial experience, or typological features - into existing generative design workflows.
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