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Toward Intelligent Industrial Informatics: A Review of Current Developments and Future Directions of Artificial Intelligence in Industrial Applications
Research Center for Data Analytics and Cognition at La Trobe University, Melbourne, Australia.
Department of Electrical Engineering and Automation, Aalto University.
Research Center for Data Analytics and Cognition at La Trobe University, Melbourne, Australia.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0069-640x
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2020 (English)In: IEEE Industrial Electronics Magazine, ISSN 1932-4529, E-ISSN 1941-0115, Vol. 14, no 2, p. 57-72Article, review/survey (Refereed) Published
Abstract [en]

Research, the universal pursuit of new knowledge, is embarking on a fresh journey into artificial intelligence (AI). Nature reports that AI arose nine places to the fourth-most popular search term and that search terms machine learning and deep learning appeared in the top 20 for the first time since 2018. It is pertinent for industrial informatics to embrace this renewed surge of interest in AI with a clear direction and purpose that engages scholars, practitioners, and professionals alike.

Place, publisher, year, edition, pages
IEEE, 2020. Vol. 14, no 2, p. 57-72
Keywords [en]
Informatics, Deep learning, Cognition, Data mining, Feature extraction, Artificial intelligence
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-80152DOI: 10.1109/MIE.2019.2952165ISI: 000543959200007Scopus ID: 2-s2.0-85087507175OAI: oai:DiVA.org:ltu-80152DiVA, id: diva2:1451593
Note

Validerad;2020;Nivå 2;2020-07-03 (alebob)

Available from: 2020-07-03 Created: 2020-07-03 Last updated: 2020-07-21Bibliographically approved

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Osipov, EvgenyVyatkin, Valeriy

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