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024 7 _a10.1007/978-981-15-6186-3
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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082 0 4 _a006.3
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100 1 _aWang, Xiaofei.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aEdge AI
_h[electronic resource] :
_bConvergence of Edge Computing and Artificial Intelligence /
_cby Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen.
250 _a1st ed. 2020.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2020.
300 _aXVII, 149 p. 38 illus., 34 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart I. Introduction and Fundamentals -- Chapter 1. Introduction -- Chapter 2. Fundamentals of Edge Computing -- Chapter 3. Fundamentals of Artificial Intelligence -- Part II. Artificial Intelligence and Edge Computing -- Chapter 4. Artificial Intelligence Applications on Edge -- Chapter 5. Artificial Intelligence Inference in Edge -- Chapter 6. Artificial Intelligence Training at Edge -- Chapter 7. Edge Computing for Artificial Intelligence -- Chapter 8. Artificial Intelligence for Optimizing Edge -- Part III. Challenges and Conclusions -- Chapter 9. Lessons Learned and Open Challenges -- Chapter 10. Conclusions.
520 _aAs an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.
650 0 _aArtificial intelligence.
650 0 _aComputer networks .
650 0 _aComputer engineering.
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputer Communication Networks.
650 2 4 _aComputer Engineering and Networks.
700 1 _aHan, Yiwen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aLeung, Victor C. M.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aNiyato, Dusit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aYan, Xueqiang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aChen, Xu.
_eauthor.
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_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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856 4 0 _uhttps://doi.org/10.1007/978-981-15-6186-3
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