@inproceedings{da61f28020a94d95b031209abfed9eb1,
title = "Machine Learning Enhanced User Interfaces for Designing Advanced Knitwear",
abstract = "The relationship between visual appearance and structure and technical properties of a knitted fabric is subtle and complex. This is an area that has been traditionally problematic within the knitting sector, understanding between technologists and designers is hindered which limits the possibility of dialogues from which design innovation can emerge. Recently there has been interest from the Human-Computer Interaction (HCI) community to narrow the gap between product design and knitwear. The goal of this article is to show the potential of predictive software design tools for fashion designers who are developing personalized advanced functionalities in textile products. The main research question explored in this article is: “How can designers benefit from intelligent design software for the manufacturing of personalized advanced functionalities in textile products?”. In particular we explored how to design interactions and interfaces that use intelligent predictive algorithms through the analysis of a case study, in which several predictive algorithms were compared in the practice of textile designers.",
keywords = "Knitwear, Machine learning, User Interface",
author = "{ten Bh{\"o}mer}, Martijn and Liang, {Hai Ning} and Difeng Yu",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 21st International Conference on Human-Computer Interaction, HCI International 2019 ; Conference date: 26-07-2019 Through 31-07-2019",
year = "2019",
doi = "10.1007/978-3-030-23528-4_30",
language = "English",
isbn = "9783030235277",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "212--219",
editor = "Constantine Stephanidis",
booktitle = "HCI International 2019 - Posters - 21st International Conference, HCII 2019, Proceedings",
address = "Germany",
}
