Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Anatolii Nikolenko"'
Autor:
Valery Druzhinin, Galina Sivyakova, Alexey Kalinin, Valerii Tytiuk, Anatolii Nikolenko, Vitaliy Vadimovich Kuznetsov, Mykhailo Kuzmenko
Publikováno v:
Diagnostyka, Vol 24, Iss 1, Pp 1-13 (2022)
In recent years, due to the tightening of competition in the global market of steel producers, the requirements for the quality of hot-rolled steel have increased. The finishing group of the rolling mill is characterized by a complex structure of mec
Externí odkaz:
https://doaj.org/article/e53e339e60a34b219288a1a2c24dfa68
Publikováno v:
Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making ISBN: 9783031162022
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64b1e4021ec6e94b0db8468aae1159df
https://doi.org/10.1007/978-3-031-16203-9_38
https://doi.org/10.1007/978-3-031-16203-9_38
Publikováno v:
Applied Aspects of Information Technology. 4:192-201
The application of deep learning convolutional neural networks for solving the problem of automated facial expression recognition and determination of emotions of a person is analyzed. It is proposed to use the advantages of the transfer approach to
Autor:
Svitlana Antoshchuk, Thanh Tran Kim, Tien Nguyen Thi Khanh, Oksana Babilunha, Anatolii Nikolenko
Publikováno v:
Herald of Advanced Information Technology. 3:362-372
Publikováno v:
Herald of Advanced Information Technology. 3:395-405
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030264734
ISDMCI
ISDMCI
To automate the process of obtaining knowledge (metadata) about the respondents of sociological surveys or questionnaires, an intelligent information technology has been developed for analyzing weakly-structured multi-dimensional medical-social data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7a007a39b54425e45f08eaf681367f0
https://doi.org/10.1007/978-3-030-26474-1_18
https://doi.org/10.1007/978-3-030-26474-1_18
Publikováno v:
2016 IEEE First International Conference on Data Stream Mining & Processing (DSMP).
Correlation-extreme method of detecting text areas in the images is proposed, which provides classification decision on the results of correlation-extreme analysis in the field of wavelet transform, which is implemented by convolutional neural networ