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Research and Analysis of the Subject Area of Deep Learning

Research and Analysis of the Subject Area of Deep Learning ISSN 0005-1055, Automatic Documentation and Mathematical Linguistics, 2019, Vol. 53, No. 3, pp. 103–113. © Allerton Press, Inc., 2019. Russian Text © The Author(s), 2019, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2: Informatsionnye Protsessy i Sistemy, 2019, No. 5, pp. 10–21. INTELLIGENT SYSTEMS V. O. Tolcheev* Moscow Power Engineering Institute, Moscow, 111250 Russia *e-mail: tolcheevvo@mail.ru Received March 11, 2019 Abstract—This paper analyzes the rapidly growing scientific direction of Deep Learning, as one of the most significant parts of artificial intelligence. Using scientometric methods, the growth rates of publications in leading countries and the level of their international cooperation are estimated. The terminological structure of the subject area is investigated and the most perspective directions of studies are revealed. We compare sci- entometric indicators of Deep Learning with another booming scientific area, Quantum Technology. The conclusion is made that publication activity on Deep Learning is growing faster. It is noted that in both these areas the United States and China are the leaders according to the number of papers. Scientometric analysis showed a fairly low level of publication activity of Russian scientists on Deep Learning and their weak involve- ment in international cooperation. Keywords: deep learning, deep neural networks, factual and http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Documentation and Mathematical Linguistics Springer Journals

Research and Analysis of the Subject Area of Deep Learning

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Publisher
Springer Journals
Copyright
Copyright © 2019 by Allerton Press, Inc.
Subject
Computer Science; Information Storage and Retrieval
ISSN
0005-1055
eISSN
1934-8371
DOI
10.3103/S000510551903004X
Publisher site
See Article on Publisher Site

Abstract

ISSN 0005-1055, Automatic Documentation and Mathematical Linguistics, 2019, Vol. 53, No. 3, pp. 103–113. © Allerton Press, Inc., 2019. Russian Text © The Author(s), 2019, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2: Informatsionnye Protsessy i Sistemy, 2019, No. 5, pp. 10–21. INTELLIGENT SYSTEMS V. O. Tolcheev* Moscow Power Engineering Institute, Moscow, 111250 Russia *e-mail: tolcheevvo@mail.ru Received March 11, 2019 Abstract—This paper analyzes the rapidly growing scientific direction of Deep Learning, as one of the most significant parts of artificial intelligence. Using scientometric methods, the growth rates of publications in leading countries and the level of their international cooperation are estimated. The terminological structure of the subject area is investigated and the most perspective directions of studies are revealed. We compare sci- entometric indicators of Deep Learning with another booming scientific area, Quantum Technology. The conclusion is made that publication activity on Deep Learning is growing faster. It is noted that in both these areas the United States and China are the leaders according to the number of papers. Scientometric analysis showed a fairly low level of publication activity of Russian scientists on Deep Learning and their weak involve- ment in international cooperation. Keywords: deep learning, deep neural networks, factual and

Journal

Automatic Documentation and Mathematical LinguisticsSpringer Journals

Published: Aug 26, 2019

References