Towards a design generation methodology

Kang Zhang; Yihang Bo; Yi Yang

doi:10.1145/3105971.3108444

Towards a design generation methodology

Kang Zhang, Yihang Bo, Yi Yang

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

2 Citations (Scopus)

Abstract

Inspired by the recent advances of deep learning and computer graphics techniques in generating sophisticated artistic styles and architectural designs, we envision a general design generation methodology that uses various specification and generative methods and tools in an integral design cycle.

Original language	English
Title of host publication	VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction
Editors	Shigeo Takahashi, Jie Li
Publisher	Association for Computing Machinery
Pages	71-72
Number of pages	2
ISBN (Electronic)	9781450352925
DOIs	https://doi.org/10.1145/3105971.3108444
Publication status	Published - 14 Aug 2017
Externally published	Yes
Event	10th International Symposium on Visual Information Communication and Interaction, VINCI 2017 - Bangkok, Thailand Duration: 14 Aug 2017 → 16 Aug 2017

Publication series

Name	ACM International Conference Proceeding Series
Volume	Part F130152

Conference

Conference	10th International Symposium on Visual Information Communication and Interaction, VINCI 2017
Country/Territory	Thailand
City	Bangkok
Period	14/08/17 → 16/08/17

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Keywords

Design
Feneration
Generative systems
Machine learning
Shape grammar

Access to Document

10.1145/3105971.3108444

Cite this

@inproceedings{84b867d0f8744bb386eed67ec32ee833,

title = "Towards a design generation methodology",

abstract = "Inspired by the recent advances of deep learning and computer graphics techniques in generating sophisticated artistic styles and architectural designs, we envision a general design generation methodology that uses various specification and generative methods and tools in an integral design cycle.",

keywords = "Design, Feneration, Generative systems, Machine learning, Shape grammar",

author = "Kang Zhang and Yihang Bo and Yi Yang",

note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 10th International Symposium on Visual Information Communication and Interaction, VINCI 2017 ; Conference date: 14-08-2017 Through 16-08-2017",

year = "2017",

month = aug,

day = "14",

doi = "10.1145/3105971.3108444",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "71--72",

editor = "Shigeo Takahashi and Jie Li",

booktitle = "VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction",

}

Zhang, K, Bo, Y & Yang, Y 2017, Towards a design generation methodology. in S Takahashi & J Li (eds), VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction. ACM International Conference Proceeding Series, vol. Part F130152, Association for Computing Machinery, pp. 71-72, 10th International Symposium on Visual Information Communication and Interaction, VINCI 2017, Bangkok, Thailand, 14/08/17. https://doi.org/10.1145/3105971.3108444

Towards a design generation methodology. / Zhang, Kang; Bo, Yihang; Yang, Yi.
VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction. ed. / Shigeo Takahashi; Jie Li. Association for Computing Machinery, 2017. p. 71-72 (ACM International Conference Proceeding Series; Vol. Part F130152).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Towards a design generation methodology

AU - Zhang, Kang

AU - Bo, Yihang

AU - Yang, Yi

PY - 2017/8/14

Y1 - 2017/8/14

N2 - Inspired by the recent advances of deep learning and computer graphics techniques in generating sophisticated artistic styles and architectural designs, we envision a general design generation methodology that uses various specification and generative methods and tools in an integral design cycle.

AB - Inspired by the recent advances of deep learning and computer graphics techniques in generating sophisticated artistic styles and architectural designs, we envision a general design generation methodology that uses various specification and generative methods and tools in an integral design cycle.

KW - Design

KW - Feneration

KW - Generative systems

KW - Machine learning

KW - Shape grammar

UR - https://www.scopus.com/pages/publications/85030775502

U2 - 10.1145/3105971.3108444

DO - 10.1145/3105971.3108444

M3 - Conference Paper published in a book

AN - SCOPUS:85030775502

T3 - ACM International Conference Proceeding Series

SP - 71

EP - 72

BT - VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction

A2 - Takahashi, Shigeo

A2 - Li, Jie

PB - Association for Computing Machinery

T2 - 10th International Symposium on Visual Information Communication and Interaction, VINCI 2017

Y2 - 14 August 2017 through 16 August 2017

ER -

Towards a design generation methodology

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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