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Bibliometric Analysis of Artificial Intelligence in Textiles.

Habiba HalepotoTao GongSaleha NoorHafeezullah Memon
Published in: Materials (Basel, Switzerland) (2022)
Generally, comprehensive documents are needed to provide the research community with relevant details of any research direction. This study conducted the first descriptive bibliometric analysis to examine the most influential journals, institutions, and countries in the field of artificial intelligence in textiles. Furthermore, bibliometric mapping analysis was also used to examine diverse research topics of artificial intelligence in textiles. VOSviewer was used to process 996 articles retrieved from Web of Science-Core Collection from 2007 to 2020. The results show that China and the United States have the largest number of publications, while Donghua University and Jiangnan University have the highest output. These three themes have also appeared in textile artificial intelligence publications and played a significant role in the textile structure, textile inspection, and textile clothing production. The authors believe that this research will unfold new research domains for researchers in computer science, electronics, material science, imaging science, and optics and will benefit academic and industrial circles.
Keyphrases
  • artificial intelligence
  • deep learning
  • wastewater treatment
  • machine learning
  • big data
  • public health
  • high resolution
  • mental health
  • systematic review
  • randomized controlled trial