International Journal of Computational Intelligence Systems

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Volume 12, Issue 2, 2019, Pages 713 - 722

Development of a Textile Coding Tag for the Traceability in Textile Supply Chain by Using Pattern Recognition and Robust Deep Learning

Authors
Kaichen Wang1, 2, *, Vijay Kumar2, Xianyi Zeng2, Ludovic Koehl2, Xuyuan Tao2, Yan Chen1
1College of Textile and Clothing Engineering, Soochow University, Suzhou, 215006, China
2ENSAIT, GEMTEX, École Centrale de Lille, Lille, 59000, France
*Corresponding author. Email: kaichen.wang@ensait.fr
Corresponding Author
Kaichen Wang
Received 25 January 2019, Accepted 24 April 2019, Available Online 9 May 2019.
DOI
10.2991/ijcis.d.190704.002How to use a DOI?
Keywords
Traceability; Textile tags; Coded yarn recognition; Deep learning; Transfer learning; Convolutional neural network
Abstract

The traceability is of paramount importance and considered as a prerequisite for businesses for long-term functioning in today's global supply chain. The implementation of traceability can create visibility by the systematic recall of information related to all processes and logistics movement. The traceability coding tag consists of unique features for identification, which links the product with traceability information, plays an important part in the traceability system. In this paper, we describe an innovative technique of product component-based traceability which demonstrates that product's inherent features—extracted using deep learning—can be used as a traceability signature. This has been demonstrated on textile fabrics, where Faster region-based convolutional neural network (Faster R-CNN) has been introduced with transfer learning to provide a robust end-to-end solution for coded yarn recognition. The experimental results show that the deep learning-based algorithm is promising in coded yarn recognition, which indicates the feasibility for industrial application.

Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
12 - 2
Pages
713 - 722
Publication Date
2019/05/09
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.190704.002How to use a DOI?
Copyright
© 2019 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Kaichen Wang
AU  - Vijay Kumar
AU  - Xianyi Zeng
AU  - Ludovic Koehl
AU  - Xuyuan Tao
AU  - Yan Chen
PY  - 2019
DA  - 2019/05/09
TI  - Development of a Textile Coding Tag for the Traceability in Textile Supply Chain by Using Pattern Recognition and Robust Deep Learning
JO  - International Journal of Computational Intelligence Systems
SP  - 713
EP  - 722
VL  - 12
IS  - 2
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.190704.002
DO  - 10.2991/ijcis.d.190704.002
ID  - Wang2019
ER  -