Neural networks to solve modern artificial intelligence tasks

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Applied Physics, Information Technologies and Engineering 2019, APITECH 2019

Год издания: 2019

Идентификатор DOI: 10.1088/1742-6596/1399/3/033058

Аннотация: Today the information technologies are increasing and improving by leaps and bounds becoming smarter and faster. And artificial intelligence is penetrating deeper and deeper in everyday life. So, artificial intelligence field is becoming more interesting for modern scientists and engineers. Artificial neural networks are used all over the world as one of the approaches that can provide with the high relevance level of resolving results of badly formalized or unformalized tasks. In this article a review of artificial neural networks development tools of different kinds is presented. Also there is a detailed description of all of them and the main features are emphasized. As a result, the table is presented that allows to make a quick compare of described tools and decide if any of them are suitable for a reader or not. © Published under licence by IOP Publishing Ltd.

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Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1399, Is. 3

Номера страниц: 33058

ISSN журнала: 17426588

Издатель: Institute of Physics Publishing

Авторы

  • Gruzenkin D.V. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Sukhanova A.V. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Novikov O.S. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Grishina G.V. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Rutskiy V.N. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Tsarev R.Y. (Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660074, Russian Federation)
  • Zhigalov K.Y. (V A Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, 65, Profsoyuznaya street, Moscow, 117997, Russian Federation, Moscow Technological Institute, Block 2, 8, Kedrova, Moscow, 117292, Russian Federation)

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