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Sökning: WFRF:(Solmaz Gürkan)

  • Resultat 1-4 av 4
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1.
  • Bartoletti, Stefania, et al. (författare)
  • Introduction and fundamentals
  • 2024
  • Ingår i: Positioning and Location-based Analytics in 5G and Beyond. - 9781119911463 ; , s. 1-18
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • This chapter introduces the book and presents the main principles and fundamentals for positioning and location-based analytics, thus effectively providing the basis for the following chapters. After a brief introduction and motivation for the book, we present the main use cases, verticals, and applications for positioning and location-based analytics. Then, we provide the technical fundamentals for understanding positioning and navigation algorithms, as well as location-based analytics. An introduction to the architectural principles is presented. Finally, an outline of the book chapters is provided.
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2.
  • Meuser, Tobias, et al. (författare)
  • Revisiting edge AI : opportunities and challenges
  • 2024
  • Ingår i: IEEE Internet Computing. - : IEEE. - 1089-7801 .- 1941-0131. ; 28:4, s. 49-59
  • Tidskriftsartikel (refereegranskat)abstract
    • Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the training and inference of machine learning models to the edge of the network. This paradigm offers the opportunity to significantly impact our everyday lives with new services such as autonomous driving and ubiquitous personalized health care. Nevertheless, bringing intelligence to the edge involves several major challenges, which include the need to constrain model architecture designs, the secure distribution and execution of the trained models, and the substantial network load required to distribute the models and data collected for training. In this article, we highlight key aspects in the development of edge AI in the past and connect them to current challenges. This article aims to identify research opportunities for edge AI, relevant to bring together the research in the fields of artificial intelligence and edge computing.
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3.
  • Meuser, Tobias, et al. (författare)
  • Revisiting Edge AI: Opportunities and Challenges
  • 2024
  • Ingår i: IEEE Internet Computing. - : Institute of Electrical and Electronics Engineers Inc.. - 1089-7801 .- 1941-0131. ; 28:4, s. 49-59
  • Tidskriftsartikel (refereegranskat)abstract
    • Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the training and inference of machine learning models to the edge of the network. This paradigm offers the opportunity to significantly impact our everyday lives with new services such as autonomous driving and ubiquitous personalized health care. Nevertheless, bringing intelligence to the edge involves several major challenges, which include the need to constrain model architecture designs, the secure distribution and execution of the trained models, and the substantial network load required to distribute the models and data collected for training. In this article, we highlight key aspects in the development of edge AI in the past and connect them to current challenges. This article aims to identify research opportunities for edge AI, relevant to bring together the research in the fields of artificial intelligence and edge computing.
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  • Resultat 1-4 av 4
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