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Titlebook: Artificial Intelligence for Fashion Industry in the Big Data Era; Sébastien Thomassey,Xianyi Zeng Book 2018 Springer Nature Singapore Pte

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樓主: Indigent
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發(fā)表于 2025-3-25 03:32:23 | 只看該作者
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發(fā)表于 2025-3-25 09:45:32 | 只看該作者
https://doi.org/10.1057/9781137009333 traceability. Further, a case-based example has been used to explain blockchain application in implementing traceability in T&C supply chain. Finally, it mentions the challenges and limitations of such blockchain-based traceability system that can be addressed through further research.
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發(fā)表于 2025-3-25 23:17:44 | 只看該作者
2366-8776 for the fashion industry.Highlights practical examples of tThis 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 st
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發(fā)表于 2025-3-26 04:06:17 | 只看該作者
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Book 2018niques 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-wo
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發(fā)表于 2025-3-26 10:35:28 | 只看該作者
Culture, Values, and Organizational Fairness forecasting, decision making in supply chain management or social networks and fashion e-marketing. Thus, this book aims to illustrate the different possibilities and advantages of artificial intelligence for the fashion industry in the big data era. This introduction chapter provides a brief description of each chapter of this book.
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發(fā)表于 2025-3-26 13:40:21 | 只看該作者
Die Abgrenzung zu anderen Vertriebsartenlogy. Also, using sensory evaluation, professional design knowledge of the designers can be fully applied to control the 2D technical space of garment design based on the perception of 3D garment virtual try-on result.
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發(fā)表于 2025-3-26 18:22:08 | 只看該作者
https://doi.org/10.1007/978-3-8349-9782-1data. The result shows that the pants’ pressure wear comfort is mainly influenced by four factors; there are thigh–hip factor, shank factor, waist factor, and crotch factor. The share of these four factors’ influence accounts for about 82.0%, and the thigh–hip factor takes up the biggest share and reaches to 44.5%.
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