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  • 1.
    Jain, Sheenam
    et al.
    Högskolan i Borås, Akademin för textil, teknik och ekonomi. Laboratoire de Génie et Matériaux Textiles (GEMTEX), ENSAIT, F-59000 Lille, France; College of Textile and Clothing Engineering, Soochow University, Suzhou 215168, China; Automatique, Génie informatique, Traitement du Signal et des Images, Université Lille Nord de France, F-59000 Lille, France.
    Giri, Chandadevi
    Högskolan i Borås, Akademin för textil, teknik och ekonomi. Laboratoire de Génie et Matériaux Textiles (GEMTEX), ENSAIT, F-59000 Lille, France; College of Textile and Clothing Engineering, Soochow University, Suzhou 215168, China; Automatique, Génie informatique, Traitement du Signal et des Images, Université Lille Nord de France, F-59000 Lille, France.
    Zeng, Xianyi
    Laboratoire de Génie et Matériaux Textiles (GEMTEX), ENSAIT, F-59000 Lille, France.
    Bruniaux, Pascal
    Laboratoire de Génie et Matériaux Textiles (GEMTEX), ENSAIT, F-59000 Lille, France.
    A Detailed Review of Artificial Intelligence Applied in the Fashion and Apparel Industry2019Ingår i: IEEE Access, E-ISSN 2169-3536Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The enormous impact of artificial intelligence has been realized in transforming the fashion and apparel industry in the past decades. However, the research in this domain is scattered and mainly focuses on one of the stages of the supply chain. Due to this, it is difficult to comprehend the work conducted in the distinct domain of the fashion and apparel industry. Therefore, this paper aims to study the impact and the significance of artificial intelligence in the fashion and apparel industry in the last decades throughout the supply chain. Following this objective, we performed a systematic literature review of research articles (journal and conference) associated with artificial intelligence in the fashion and apparel industry. Articles were retrieved from two popular databases ‘‘Scopus’’ and ‘‘Web of Science’’ and the article screening was completed in five phases resulting in 149 articles. This was followed by article categorization which was grounded on the proposed taxonomy and was completed in two steps. First, the research articles were categorized according to the artificial intelligence methods applied such as machine learning, expert systems, decision support system, optimization, and image recognition and computer vision. Second, the articles were categorized based on supply chain stages targeted such as design, fabric production, apparel production, and distribution. In addition, the supply chain stages were further classified based on business-to-business (B2B) and business-to-consumer (B2C) to give a broader outlook of the industry. As a result of the categorizations, research gaps were identified in the applications of AI techniques, at the supply chain stages and from a business (B2B/B2C) perspective. Based on these gaps, the future prospects of the AI in this domain are discussed. These can benefit the researchers in academics and industrial practitioners working in the domain of the fashion and apparel industry.

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