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Virginia Tech

Re_Imaged: Reimaging architecture through artificially intelligent generated images

Abstract

dc:description.abstract

Artificial Intelligence is a machine learning technique that exists everywhere in our day-to-day life. From a simple Google search that provides answers to any questions, to autocorrect suggestions provided while writing emails, we encounter AI in every next phase of our life. Humans have developed an invisible trust in AI that remains unrecognized. Artificial intelligence (AI) development in architecture has been a protracted and intriguing process. Recent advances in text-to-image generating software powered by AI have proven to be an efficient tool for architects to visualize their designs with a different perspective and enhance the thinking process. However, the lack of the tool's ability to capture the designer's integrity has shown the requirement for human involvement. This thesis claims that human decision-making skills remain crucial despite AI-augmented design's benefits. By conducting a comparative analysis between human-developed architecture and AI-augmented designs through the process of AI text-to-image generating tool Stable Diffusion, the thesis argues that human brain involvement is necessary due to the lack of Stable Diffusion's ability to understand architectural drawings and elements, the ability to representing architectural depth through spaces and emotions, and its inadequate learning from the past design experiences.

Degree

thesis:*
Name thesis:degree_name
Master of Architecture
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Architecture
Department dc:contributor.department
Architecture
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gajjar, Charmi Praful
Chair dc:contributor.committeechair
  • Ishida, Aki
Committee members dc:contributor.committeemember
  • Bedford, Joseph
  • Becker, Edward Gentry
  • He, Chenxuan

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:37892
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/115901

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Gajjar, Charmi Praful. Re_Imaged: Reimaging architecture through artificially intelligent generated images. masters thesis, Virginia Tech, 2023. http://hdl.handle.net/10919/115901