Abstract
This paper presents a deep learning approach to measuring brand store image and generating positioning maps. The rise of signature brand stores can be explained in terms of brand identity. Store design and architecture have been highlighted as effective communicators of brand identity and position but, in terms of spatial environment, have been studied solely using qualitative approaches. This study adopted a deep learning-based image classification model as an alternative methodology for measuring brand image and positioning, which are conventionally considered highly subjective. The results demonstrate that a consistent, coherent, and strong brand identity can be trained and recognized using deep learning technology. A brand positioning map can also be created based on predicted scores derived by deep learning. This paper also suggests wider uses for this approach to branding and architectural design.
Original language | English |
---|---|
Title of host publication | RE |
Subtitle of host publication | Anthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 |
Editors | Dominik Holzer, Walaiporn Nakapan, Anastasia Globa, Immanuel Koh |
Publisher | The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) |
Pages | 691-698 |
Number of pages | 8 |
ISBN (Electronic) | 9789887891741 |
Publication status | Published - 2020 |
Event | 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 - Bangkok, Thailand Duration: 2020 Aug 5 → 2020 Aug 6 |
Publication series
Name | RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 |
---|---|
Volume | 2 |
Conference
Conference | 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 |
---|---|
Country/Territory | Thailand |
City | Bangkok |
Period | 20/8/5 → 20/8/6 |
Bibliographical note
Funding Information:This work was supported by the BK21 Plus funded by the Ministry of Education of Korea.
Publisher Copyright:
© 2020 and published by the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Building and Construction