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Machine Learning in Architecture

Wang, Qingling LU (2022) AAHM10 20221
Department of Architecture and Built Environment
Abstract
The development of image-based machine learning technology brings new ways of how we use and produce images. Due to the significant reliance on images and drawings, machine learning technology might achieve new potentials for the architecture discipline. My thesis explored these potentials through conducting experiments. In the first part of my thesis, I used the image-based machine learning algorithm to conduct facade and church generation experiments to discover the relationship between architect, image, and algorithm. In the second part, I evaluated the quality of generated results and considered the future potential of using machine learning technology in architecture.
Please use this url to cite or link to this publication:
author
Wang, Qingling LU
supervisor
organization
alternative title
The new relationship between architect, image and tool
course
AAHM10 20221
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Machine learning；Artificial intelligence；Generative adversarial networks；Church
language
English
id
9085943
date added to LUP
2022-06-09 10:24:58
date last changed
2022-06-09 10:24:58
@misc{9085943,
  abstract     = {{The development of image-based machine learning technology brings new ways of how we use and produce images. Due to the significant reliance on images and drawings, machine learning technology might achieve new potentials for the architecture discipline. My thesis explored these potentials through conducting experiments. In the first part of my thesis, I used the image-based machine learning algorithm to conduct facade and church generation experiments to discover the relationship between architect, image, and algorithm. In the second part, I evaluated the quality of generated results and considered the future potential of using machine learning technology in architecture.}},
  author       = {{Wang, Qingling}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Machine Learning in Architecture}},
  year         = {{2022}},
}