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Artificial Intelligence for Fashion Industry in the Big Data Era

Author(s):
Publisher:

Springer

Pages: 288
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AVAILABLE FORMATS

Hardcover - 9789811300790

28 May 2018

$159.00

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Ebook - 9789811300806

16 May 2018

$119.00

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This book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges....

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This book provides an overview of current issues and challenges in the fashion industry and an update on data-driven artificial intelligence (AI) techniques and their potential implementation in response to those challenges. Each chapter starts off with an example of a data-driven AI technique on a particular sector of the fashion industry (design, manufacturing, supply or retailing), before moving on to illustrate its implementation in a real-world application

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Provides an overview of current issues in the fashion industry
 
Includes updates on existing artificial intelligence (AI) techniques suitable for the fashion industry
 
Highlights practical examples of the implementation of AI techniques in the fashion industry 

AI based fashion sales forecasting methods in big data era
Enhanced Predictive Models for Purchasing in the Fashion Field by Applying Regression Trees Equipped with Ordinal Logistic Regression
A Data Mining Based Framework for Multi-Item Markdown Optimization
Social Media Analytics for decision support in Fashion Buying Processes
Review of Artificial Intelligence Applications in Garment Manufacturing
AI for Apparel Manufacturing in Big Data Era: A Focus on Cutting and Sewing
A Discrete Event Simulation Model with Genetic Algorithm Optimization for Customized Textile Production Scheduling
An intelligent fashion replenishment system based on data analytics and expert judgement
Blockchain based secured traceability system for textile and clothing supply chain
Artificial intelligence applied to multisensory studies of textile products
Evaluation of Fashion Design Using Artificial Intelligence Tools
Garment wearing comfort analysis using data mining technology
Garment fit evaluation using machine learning technology.
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Sébastien Thomassey (PhD) is currently associate professor at the “Ecole Supérieure des Arts et Industries Textiles” (ENSAIT) and the GEMTEX laboratory. He gained an MSc(Eng.) in textile and clothing production from the ENSAIT in 1999, an MSc in advanced data analysis from the Lille I University in 1999 and a PhD in automation and information technology from the Lille I University in 2002. He was an engineer in R&D at the French technical center for the textile/clothing, IFTH, from 1999 to 2002 and a researcher at the Mathematic and Operational Research Laboratory of the Polytechnic Institute of Mons in Belgium in 2003. His research is mainly focused on the implementation of soft computing and data mining...

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Sébastien Thomassey (PhD) is currently associate professor at the “Ecole Supérieure des Arts et Industries Textiles” (ENSAIT) and the GEMTEX laboratory. He gained an MSc(Eng.) in textile and clothing production from the ENSAIT in 1999, an MSc in advanced data analysis from the Lille I University in 1999 and a PhD in automation and information technology from the Lille I University in 2002. He was an engineer in R&D at the French technical center for the textile/clothing, IFTH, from 1999 to 2002 and a researcher at the Mathematic and Operational Research Laboratory of the Polytechnic Institute of Mons in Belgium in 2003. His research is mainly focused on the implementation of soft computing and data mining techniques for modeling, simulation, supply and production chain optimization, forecasting sales of clothing products, clustering, classification and decision support systems for textile/apparel industry. His work has been published in refereed journals, such as Applied Soft Computing, Decision Support Systems, European Journal of Operational Research, and the International Journal of Production Economics,. He is actively involved in research projects in production and supply chain management, sales forecasting and clustering/classification of fashion products.
 
He has also participated in various European and national research projects related to sustainable textile design and management, simulation and optimization of manufacturing units, clustering and classification of 3D morphologies for intelligent sizing systems, and sales-forecast-based simulation in pricing strategy.

X.Y. Zeng received the B.Eng. degree from the Department of Science and Technology, Tsinghua University, Beijing, China, in 1986, and the Ph.D. degree from the Centre d’Automatique, Université des Sciences et Technologies de Lille, Villeneuve d’Ascq, France, in 1992. He is currently a Full Professor with the French Engineer School, Ecole Nationale Supérieure des Arts et Industries Textiles (ENSAIT), Roubaix, France. Since 2000, he has led the Human-Centered Design research team in ENSAIT. He has published two scientific books, more than 260 papers at reviewed international journals, and international conference proceedings. His research interests include: 1) intelligent decision support systems for fashion and material design, 2) modeling of human perception and cognition on industrial products, 3) intelligent wearable systems.

Dr. Zeng is currently an Associate Editor of International Journal of Computational Intelligence System and Journal of Fiber Bioengineering and Informatics, a Guest Editor of Special Issues for six international journals, and a senior member of IEEE. He has organized 12 international conferences and workshops since 1996. Since 2000, he has been the leader of three European projects, four national research projects funded by the French government, three bilateral research cooperation projects, and more than 20 industrial projects.




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