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Research Article
A Study on Applications of Machine Learning Concepts in Textile Industry
Dr.J.B.Jona1
S.A.Gunasekaran2
Deetchika3
Mrithika4
Roshini5
1 Associate Professor, Dept. of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India. 2 Assistant Professor, Dept. of Computer Applications, Coimbatore Institute of Technology, Tamilnadu, India. 345 Students, Dept. of Decision and Computing Sciences, Coimbatore Institute of Technology, Tamilnadu, India.
Published Online: May-June 2022
Pages: 428-431
Cite this article
No DOIReferences
1. Implementation of an Automated Manufacturing Process for Smart Clothing: The Case Study of a Smart Sports Bra BySuhyun Lee,
Soo Hyeon Rho, Sojung Lee, Jiwoong Lee, Sang Won Lee, Daeyoung Lim, WonyoungJeong. https://www.mdpi.com/2227-
9717/9/2/289/html.
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Commun. Converg. Eng. 2020, 18, 61–68. [Google Scholar]
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Scholar]
4. Kondratas, A. Robotic gripping device for garment handling operations and its adaptive control. Fibers Text. East. Eur. 2005, 13,
84–89. [Google Scholar]
5. LesyaSviruk, SnizhanaKurochka, Oksana Zakharkevich& Svetlana Kuleshova, Applicaion of Deep Learning in Apparel Design.
6. Amparo Alonso-Betanzos, Sun-Kuk Noh, Recycled Clothing Classification System Using Intelligent IoT and Deep Learning with
AlexNet -Amparo Alonso-Betanzos, Recycled Clothing Classification System Using Intelligent IoT and Deep Learning with AlexNet
7. Vuruskan, A.; Ince, T.; Bulgun, E.; Guzelis, C. Intelligent fashion styling using genetic search and neural classification. Int. J. Cloth.
Sci. Technol.
8. Wei, B.; Hao, K.; Tang, X.S.; Ren, L. Fabric defect detection based on faster RCNN. In Advances in Itelligent Systems and
Computing; Springer: Cham
9. The Swedish School of Textiles, University of Boras, S-50190 Boras, Sweden, Garment Categorization Using Data Mining
Techniques.
10. Bengio Y., LeCun Y., & Hinton G. (2015). Deep Learning. Nature, No. 521, (2015), pp. 436-444. doi:10.1038/nature14539.
11. Romaniuk O. (2017). Fashion and Technology: How Deep Learning Can Create an Added Value in Retail. [Online]. Available:
http://labs.eleks.com/2017/05/fashion-technology-deep-learning-can-create-added-value-retail.html [2017-08-03].
Soo Hyeon Rho, Sojung Lee, Jiwoong Lee, Sang Won Lee, Daeyoung Lim, WonyoungJeong. https://www.mdpi.com/2227-
9717/9/2/289/html.
2. Kim, J.C.; Moon, I.Y. A study on smart factory construction method for efficient production management in sewing industry. J. Inf.
Commun. Converg. Eng. 2020, 18, 61–68. [Google Scholar]
3. Nayak, R.; Padhye, R. Automation in Garment Manufacturing; Woodhead Publishing: Duxford, UK, 2018; pp. 1–290. [Google
Scholar]
4. Kondratas, A. Robotic gripping device for garment handling operations and its adaptive control. Fibers Text. East. Eur. 2005, 13,
84–89. [Google Scholar]
5. LesyaSviruk, SnizhanaKurochka, Oksana Zakharkevich& Svetlana Kuleshova, Applicaion of Deep Learning in Apparel Design.
6. Amparo Alonso-Betanzos, Sun-Kuk Noh, Recycled Clothing Classification System Using Intelligent IoT and Deep Learning with
AlexNet -Amparo Alonso-Betanzos, Recycled Clothing Classification System Using Intelligent IoT and Deep Learning with AlexNet
7. Vuruskan, A.; Ince, T.; Bulgun, E.; Guzelis, C. Intelligent fashion styling using genetic search and neural classification. Int. J. Cloth.
Sci. Technol.
8. Wei, B.; Hao, K.; Tang, X.S.; Ren, L. Fabric defect detection based on faster RCNN. In Advances in Itelligent Systems and
Computing; Springer: Cham
9. The Swedish School of Textiles, University of Boras, S-50190 Boras, Sweden, Garment Categorization Using Data Mining
Techniques.
10. Bengio Y., LeCun Y., & Hinton G. (2015). Deep Learning. Nature, No. 521, (2015), pp. 436-444. doi:10.1038/nature14539.
11. Romaniuk O. (2017). Fashion and Technology: How Deep Learning Can Create an Added Value in Retail. [Online]. Available:
http://labs.eleks.com/2017/05/fashion-technology-deep-learning-can-create-added-value-retail.html [2017-08-03].
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