DEMOCRATISING DESIGN through SURROGATE MODEL CONVOLUTIONAL NEURAL NETWORKS of COMPUTER AIDED DESIGN REPOSITORIES

Research output: Contribution to conferenceConference Paperpeer-review

3 Citations (Scopus)

Abstract

The capability to manufacture at home is continually increasing with technologies, such as 3D printing. However, the ability to design products suitable for manufacture and use remains a highly-skilled and knowledge intensive activity. This has led to 'content creators' providing vast repositories of manufacturable products for society, however challenges remain in the search & retrieval of models. This paper presents the surrogate model convolutional neural networks approach to search and retrieve CAD models by mapping them directly to their real-world photographed counterparts.

Original languageEnglish
Pages1285-1294
Number of pages10
DOIs
Publication statusPublished - 2020
Event16th International Design Conference, DESIGN 2020 - Virtual, Online
Duration: 26 Oct 202029 Oct 2020

Conference

Conference16th International Design Conference, DESIGN 2020
CityVirtual, Online
Period26/10/2029/10/20

Bibliographical note

Funding Information:
The work reported in this paper has been undertaken as part of the UKRI NCC (EP/R513556/1) and EPSRC Trans-disciplinary Engineering (EP/R013179/1) grants.

Publisher Copyright:
© The Author(s), 2020. Published by Cambridge University Press.

Keywords

  • 3D printing
  • computer-aided design (CAD)
  • convolutional neural networks
  • design informatics
  • surrogate models

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