Titre :

Garment fit evaluation using neural networks technology

Auteur(s) :

Liu, Kaixuan [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Wang, R. L. [Auteur]
Hao, X. Y. [Auteur]
Zhu, Chun [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Zhou, S. M. Z. [Auteur]
Zeng, Xianyi [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Tao, Xuyuan [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bruniaux, Pascal [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Wang, J. P. [Auteur]

Titre de la revue :

Journal of the Textile Institute

Nom court de la revue :

J. Text. Inst.

Date de publication :

2023-04-18

ISSN :

0040-5000

Mot(s)-clé(s) en anglais :

Fit evaluation
data learning
artificial neural networks

Discipline(s) HAL :

Sciences de l'ingénieur [physics]

Résumé en anglais : [en]

At present, garment e-commerce is developing rapidly, and the number of online shopping has increased significantly. In this context, the intelligent evaluation technology of garment fit is particularly important. Fit is ...
Lire la suite >At present, garment e-commerce is developing rapidly, and the number of online shopping has increased significantly. In this context, the intelligent evaluation technology of garment fit is particularly important. Fit is the most basic requirement in the process of human dressing. It is of great significance to study the relationship between garment fit and human movement, garment structure, and fabric properties. In this article, we propose a garment fit evaluation model based on back propagation artificial neural network. This method realizes the evaluation of garment fit without any tryout. The inputs of the model are the anthropometric data, garment pattern and fabric properties, while the output is the prediction result of garment fit (fit or unfit). In order to build and train the model, the input and output data were obtained by experiment. And a total of 284 experimental samples were obtained. Through the real try-on test, the results revealed that this approach can effectively evaluate the fit of garment. It introduces new ideas and methods for the intelligent evaluation of garment fit, and has a certain reference value for the research of intelligent evaluation technology of garment fit.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

Université de Lille
ENSAIT
Junia HEI

Collections :

• Génie des matériaux textiles (GEMTEX) - ULR 2641

Date de dépôt :

2023-06-20T12:14:54Z
2024-02-20T10:54:23Z