Deep learning UI design patterns of mobile apps

User interface (UI) is one of the most important components of a mobile app and strongly influences users' perception of the app. However, UI design tasks are typically manual and time-consuming. This paper proposes a novel approach to (semi)-automate those tasks. Our key idea is to develop and...

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Bibliographic Details
Published in2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER) pp. 65 - 68
Main Authors Nguyen, Tam The, Vu, Phong Minh, Pham, Hung Viet, Nguyen, Tung Thanh
Format Conference Proceeding
LanguageEnglish
Published New York, NY, USA ACM 27.05.2018
SeriesACM Conferences
Subjects
Bars
Deep Learning
Generative adversarial networks
Layout
Machine learning
Natural languages
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UI Design Patterns
User Interface
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Summary:User interface (UI) is one of the most important components of a mobile app and strongly influences users' perception of the app. However, UI design tasks are typically manual and time-consuming. This paper proposes a novel approach to (semi)-automate those tasks. Our key idea is to develop and deploy advanced deep learning models based on recurrent neural networks (RNN) and generative adversarial networks (GAN) to learn UI design patterns from millions of currently available mobile apps. Once trained, those models can be used to search for UI design samples given user-provided descriptions written in natural language and generate professional-looking UI designs from simpler, less elegant design drafts.
ISBN:9781450356626
1450356621
DOI:10.1145/3183399.3183422