THE ELECTRONIC SCIENTIFIC JOURNAL "YOUNG SCIENCE OF SIBERIA"

ASSESSMENT AND PROSPECTS FOR THE DEVELOPMENT OF ARTIFICIAL NEURAL NETWORK DEEP LEARNING

Authors: 
Receipt date: 
15.06.2020
Bibliographic description of the article: 

Pechkin A.D., Kirillova T. K. Ocenka i perspektivy razvitiya glubokogo obucheniya iskusstvennyh nejronnyh setej [Assessment and prospects for the development of artificial neural network deep learning]. The electronic scientific journal "Young science of Siberia", 2021, no.1. [Accessed 17/05/21]

Year: 
2021
Journal number: 
УДК: 
004.048
Article File: 
Abstract: 

This article provides an overview of the development of artificial neural network deep learning; its main types are considered. Now, deep learning continues to develop and the use of new methods and learning strategies allows you to increase the speed and accuracy of these algorithms. It is also worth mentioning that these algorithms can make decisions that are superior to the work of a biological neural network. In addition, the development of technologies allows us to speed up their work. The analysis of the state of this technology is carried out, the advantages and disadvantages of the current moment and prospects for the future of deep learning are identified

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