Journals
Books
Articles by keyword сверточные нейронные сети
Recognition of images with convolution and fuzzy neural networks
N.M. Novikova - Dr. Sc. (Eng.), Professor, Voronezh State University. E-mail: novnelly839@gmail.com V.M. Dudenkov - Post-graduate Student, Voronezh State University. E-mail: vldud@mail.ru
Convolutional neural networks application for dust particles detection and recognition on microscopy images
A.N. Kokoulin - Ph.D. (Eng.), Associate Professor, Perm National Research Polytechnic University. E-mail:liga_asu@mail.ru
A convolutional fuzzy neural network for classification tasks
K.P. Korshunova - Post-graduate Student, Department of Computer Facilities, The Branch of National Research University "Moscow Power Engineering Institute" in Smolensk E-mail: ksenya-kor@mail.ru
Hierarchical pyramidal subsampling in deep convolutional networks for visual pattern recognition

A. E. Averyanikhin, A. I. Vlasov, E. V. Evdokimova Department IU4 of Designing and Technology of Electronic Equipment, Bauman Moscow State Technical University (Moscow, Russia)

Detection of anthropometric face points based on deep learning methods to recognize emotions

O.V. Melnik – Dr. Sc. (Eng.), Professor, Department “Information-Measuring and Biomedical Engineering”,  Ryazan State Radio Engineering University n.a. acad. V.F. Utkin

E-mail: omela111@yandex.ru

V.A. Sablina – Ph.D. (Eng.), Associate Professor, Department “Electronic Computing Machines”,  Ryazan State Radio Engineering University n.a. acad. V.F. Utkin

E-mail: flyingvictory@mail.ru

A.V. Savin – Post-graduate Student, Department “Electronic Computing Machines”, 

Ryazan State Radio Engineering University n.a. acad. V.F. Utkin

E-mail: savin.alex@mail.ru

A.B. Borschev – Undergraduate, Department “Electronic Computing Machines”, 

Ryazan State Radio Engineering University n.a. acad. V.F. Utkin

Rich feature hierarchies for accurate object detection and semantic segmentation

A.Y. Virasova1, D.I. Klimov2, O.E. Khromov3, I.R. Gubaidullin4, V.V. Oreshko5

1−5 JSC "Russian Space Systems" FKA "Roscosmos" (Moscow, Russia)

The use of artificial neural networks on examples of large IT projects

N.S. Konnova – PhD (Eng.), Associate Professor, Bauman Moscow State Technical University

E-mail: nkonnova@bmstu.ru

Automatic speaker age and gender recognition based on deep neural networks

M.V. Markitantov – Junior Research Scientist,
St. Petersburg Institute for Informatics and Automation of RAS

A.A. Karpov – Dr.Sc.(Eng.), Associate Professor, Main Research Scientist,
St. Petersburg Institute for Informatics and Automation of RAS

Development of a neural network model for detecting objects in a video stream

E.S. Budaev1, S.S. Mikhailova2, I.S. Evdokimova3, E.A. Khalmakshinov4

1,2 Financial University under the Government of the Russian Federation (Moscow, Russia)

3,4 East Siberian State University of Technology and Management (Ulan-Ude, Russia)

Monitoring the state of iron products based on computer vision systems

N.A. Andriyanov1, A.A. Volnenko2, V.E. Dementiev3

1,2 Financial University under the Government of the Russian Federation (Moscow, Russia)

3 Ulyanovsk State Technical University (Ulyanovsk, Russia)

Improvement of intelligent data processing methods for monitoring elements of transport infrastructure

M.A. Ludagovskaya1, N.A. Antonov2, M.A. Kabanov3, S.V. Chernomordov4

1 Russian University of Transport (MIIT) (Moscow, Russia)

2-4 Bunin Yelets State University (Yelets, Russia)

1 m.ludagovskaya@gmail.com; 2 nikolayantonov888@yandex.ru; 3 nicsor2010@yandex.ru; 4 chernomor96@list.ru

Improvement of intelligent data processing methods for monitoring elements of transport infrastructure

M.A. Ludagovskaya1, N.A. Antonov2, M.A. Kabanov3, S.V. Chernomordov4

1 Russian University of Transport (MIIT) (Moscow, Russia)

2-4 Bunin Yelets State University (Yelets, Russia)

1 m.ludagovskaya@gmail.com; 2 nikolayantonov888@yandex.ru; 3 nicsor2010@yandex.ru; 4 chernomor96@list.ru

Methods for predicting failures of functional elements of rocket and space technology products using visual decomposition and machine learning

A.Yu. Viryasova1, A.I. Vlasov2, D.I. Klimov3, T.T. Mamedov4, A.P. Myagkov5

1,3–5 JSC "Russian Space Systems" (Moscow, Russia)

2 Bauman Moscow State Technical University (Moscow, Russia)

1 virnastya@yandex.ru, 2 vlasovai@bmstu.ru, 3 klimov.di@spacecorp.ru,

4 mamedov.tt@spacecorp.ru, 5 contact@spacecorp.ru

Modern methods of computer vision and their practical application in the problem of defectoscopy of integrated circuits

A.Yu. Shafigullina1, D.I. Klimov2, T.T. Mamedov3, I.R. Gubaidullin4

1–4 Joint Stock Company "Russian Space Systems" (Moscow, Russia)

2 National Research University "Moscow Power Engineering Institute" (Moscow, Russia)

1 postgraduate contact@spacecorp.ru, 2 klimov.di@spacecorp.ru,
3 mamedov.tt@spacecorp.ru, 4 gubaidullin.ir@spacecorp.ru

A New Method for Integrating a Deep Learning Module into Special Object Classification Software

P.O. Arkhipov1, S.L. Philippskih2, M.V. Tsukanov3

1–3 Branch Director, Orel Branch of the Federal Research Center “Computer Science and Control” of the RAS
(Orel, Russia)
1 arpaul@mail.ru, 2 philippsl@mail.ru, 3 tsukanov.m.v@yandex.ru

The use of neural network technologies in the design of printed circuit boards

A.V. Arkhipov1, K.A. Muravyov2, A.A. Solodnjakov3, I.S. Potanin4

1–4 Bauman Moscow State Technical University (Moscow, Russia)

2 muravyov@bmstu.ru