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Assessing the Potential Applications...

ProQuest Information and Learning Co.

Assessing the Potential Applications of Deep Learning in Design.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Assessing the Potential Applications of Deep Learning in Design./
作者:	Mahankali, Ranjeeth.
面頁冊數:	1 online resource (85 pages)
附註:	Source: Masters Abstracts International, Volume: 57-05.
標題:	Architecture. -
電子資源:	click for full text (PQDT)
ISBN:	9780355850567

Assessing the Potential Applications of Deep Learning in Design.
Mahankali, Ranjeeth.

Assessing the Potential Applications of Deep Learning in Design. - 1 online resource (85 pages)

Source: Masters Abstracts International, Volume: 57-05.

Thesis (Master's)--University of Washington, 2018.

Includes bibliographical references

The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn. Amidst all the excitement surrounding this field, there are several prototypes being made, most of which are narrow, single purpose applications of deep learning technologies. This thesis takes a step back to establish a broader understanding of the new class of algorithms that deep learning offers. Beginning with the observation that architectural design workflow is often characterized by several representational transformations as projects grow in resolution and complexity, from sketching to detailed drawings or models, this research developed a series of deep learning prototypes that illustrate the potential application of this technology in the larger design workflow. This paper discusses the performance of these prototypes, identifies the challenges for integrating deep learning in practical design applications. This paper also suggests some ways in which these technologies might affect how the design process is carried out.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355850567Subjects--Topical Terms:

555123
Architecture.
Index Terms--Genre/Form:

554714
Electronic books.

Assessing the Potential Applications of Deep Learning in Design.
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500 $a Source: Masters Abstracts International, Volume: 57-05.
500 $a Adviser: Brian R. Johnson.
502 $a Thesis (Master's)--University of Washington, 2018.
504 $a Includes bibliographical references
520 $a The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn. Amidst all the excitement surrounding this field, there are several prototypes being made, most of which are narrow, single purpose applications of deep learning technologies. This thesis takes a step back to establish a broader understanding of the new class of algorithms that deep learning offers. Beginning with the observation that architectural design workflow is often characterized by several representational transformations as projects grow in resolution and complexity, from sketching to detailed drawings or models, this research developed a series of deep learning prototypes that illustrate the potential application of this technology in the larger design workflow. This paper discusses the performance of these prototypes, identifies the challenges for integrating deep learning in practical design applications. This paper also suggests some ways in which these technologies might affect how the design process is carried out.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Architecture. $3 555123
650 4 $a Artificial intelligence. $3 559380
650 4 $a Design. $3 595500
655 7 $a Electronic books. $2 local $3 554714
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690 $a 0800
690 $a 0389
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710 2 $a University of Washington. $b Architecture. $3 1182494
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