Defining the main features of clothing to apply deep learning in apparel design
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Дата
2018-01
Автори
Zakharkevich, Oksana
Kuleshova, Svetlana
Slavinskaya, Alla
Vovk, Julia
Назва журналу
Номер ISSN
Назва тому
Видавець
Vlakna a Textil
Анотація
The paper is devoted to defining the features of clothing to apply deep learning in apparel
design. The images of women's outerwear were selected with the help of reverse image search.
The images of women's duffle coats, coats and suit jackets were selected. The selected material was
sampled for the next categorical principal components analysis and general assessment of differences that
are caused by specific features of garments. It was revealed that similarity search might be used to
perform the selection of models to define the typical design solutions. However, a process of defining
the solutions cannot be automated yet. The indicators of clusters, which were revealed in the result
of the categorical principal components analysis, define the structure of the database for the deep learning.
Based on the results of performed online survey, it was considered advisable to use as labels specific
features of the particular garment type rather than its name. Each label refers to one of the main features
of a garment type.
Опис
Ключові слова
deep learning, deep learning, similarity search, similarity search, features of garment, features of garment, garment type, garment type
Бібліографічний опис
Zakharkevich О. Defining the main features of clothing to apply deep learning in apparel design / О. Zakharkevich, A. Selezneva, S. Kuleshova, A. Slavinskaya, J. Vovk, G. Shvets // Vlakna a Textil. – Slovakia, 2018. – Vol. 25 (№ 4). – P. 103-109.