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To The Problem of the Handwriting Characters Recognition
P. 18–24.
Istratov Anatoly Urievich, Fedin N. A.
The article discusses development of the segmented characters classifier of the Russian alphabet and of the Arabic numerals on the basis of block neural network structures including the plurality of blocks for each individual character recognition and for the synthesis block decision.
In book
* 2. , M.: HSE, 2014.
Springer, 2026.
Added: October 19, 2026
Алкзир Н., Yarykina n., Nikolaev D. et al., Neuroscience and Behavioral Physiology 2024
Added: April 28, 2025
Ullah T., Siraj A. H., Umer Mukhtar Andrabi et al., , in: 2022 VIII International Conference on Information Technology and Nanotechnology (ITNT).: IEEE, 2022. P. 1–7.
Added: March 20, 2025
Hlib Nekrasov, Aleksandr Belov, , in: International IoT, Electronics and Mechatronics Conference, Volume 2. Proceedings of IEMTRONICS 2024. LNEE, volume 1228Vol. 1228.: Springer Publishing Company, 2025. P. 379–395.
Added: January 26, 2025
Yasnitsky L., Plotnikova E. G., Прикладная информатика 2024 Т. 19 № 5 С. 88–100
Outliers in statistical data, which are the result of erroneously collected information, are often an obstacle to the successful application of machine learning methods in many subject areas. The presence of outliers in training data sets reduces the accuracy of machine learning models, and in some cases, makes the application of these methods impossible. Currently ...
Added: November 29, 2024
Milovidov S., Artnodes 2024 No. 33 P. 1–9
This article employs a case‐study method to investigate the artivism neural network community concentrated on Twitter (since renamed X), which has been ideologically influenced by the content policy and limitations of OpenAI. Today, many young artists using machine learning technologies in their artworks (Midjourney, Stable Diffusion, Kandinsky) note that despite significant progress in the field ...
Added: February 1, 2024
Kosmachev A., Задорожникова А. А., Perov A., В кн.: БОЛЬШИЕ ДАННЫЕ Материалы I Международного форума (Новосибирск, 16–18 ноября 2022 года).: Новосибирск: Новосибирский государственный университет экономики и управления «НИНХ», 2023.
The article discusses the basic concepts and terms used in steganography, substantiates the relevance of the problem of steganalysis, discusses the use of deep neural networks in the tasks of steganalysis on digital images. A comparative analysis and description of the most effective convolutional network architectures for solving the task is performed. ...
Added: January 26, 2024
I. K. Kusakin, Fedorets O. V., A. Y. Romanov, Scientific and Technical Information Processing 2023 Vol. 50 No. 3 P. 176–183
This paper discusses modern approaches to natural language processing and the application of machine learning models to the task of classifying short scientific texts in Russian. This study is devoted to the analysis of methods for vectorization of textual information, selection of a model for scientific paper clas- sification, and training of linguistic model BERT ...
Added: November 4, 2023
Penskaja E., Khachaturyan L., Филологические науки. Научные доклады высшей школы 2023 № 5 С. 160–165
The article examines the current trends in workingwith digital forms of handwritten heritage on the history of Russian literature of the second half of the 19 — mid-20 century. The process of forming virtual archives is analyzed as a gradual accumulation of the “big date” of scientific research — an unrecognized information array of raster ...
Added: October 30, 2023
Искандеров Ю. М., Катарушкин Б. Е., Ершов А. А., Информатизация и связь 2020 № 2 С. 46–51
Aim. Currently, when creating intelligent information systems in various fields of practical activity, machine learning methods are used. The article shows the possibilities of using these methods in automating the detection of obstacles in the interest of improving safety and reducing the number of emergencies at level crossings. Materials and methods. The article discusses advanced ...
Added: September 15, 2023
Fabrykant M., Социодиггер 2023 Т. 4 № 5-6
Обсуждаются возможные причины доверия к ChatGPT. Делается вывод, что основная приична в том, что ChatGPT представляют собой наиболее точный из доступных эквивалентов коммуникации с обществом в целом. ...
Added: August 23, 2023
[б.и.], 2023.
Addressing problems in different science and engineering disciplines often requires solving optimization problems, including via machine learning from large training data. One class of methods has recently gained significant attention for problems in computer vision and visual computing: coordinate-based neural networks parameterizing a field, such as a neural network that maps a 3D spatial coordinate ...
Added: July 18, 2023
Pantiukhin D., Информатика и образование 2023 Т. 38 № 1 С. 55–63
The problem of neural network vulnerability has been the subject of scientific research and experiments for several years. Adversarial attacks are one of the ways to “trick” a neural network, to force it to make incorrect classification decisions. The very possibility of adversarial attack lies in the peculiarities of machine learning of neural networks. The ...
Added: April 14, 2023
Vladimir V. Klinshov, Kirillov S., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2022 Vol. 106 No. 6 Article L062302
Neural mass models is a general name for various models describing the collective dynamics of large neural
populations in terms of averaged macroscopic variables. Recently, the so-called next-generation neural mass
models have attracted a lot of attention due to their ability to account for the degree of synchrony. Being exact
in the limit of infinitely large number of ...
Added: January 24, 2023
Vladimir V. Klinshov, Kovalchuk A., Franović I. et al., Chaos, Solitons and Fractals 2022 Vol. 158 Article 112011
Rate chaos is a collective state of a neural network characterized by slow irregular fluctuations of firing rates of
individual neurons.We study a sparsely connected network of spiking neuronswhich demonstrates three different
scenarios for the emergence of rate chaos, based either on increasing the synaptic strength, increasing the
synaptic integration time, or clustering of the excitatory synaptic connections. ...
Added: January 24, 2023
Muratova A., Ignatov D. I., Mitrofanova E., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 297–299.
This is the extended abstract of a case study on demographic sequences analysis by machine learning and data mining methods. ...
Added: November 1, 2022
Ali N., Alshahrani A., Alghamdi A. M. et al., Applied Sciences (Switzerland) 2022 Vol. 12 No. 13 Article 6378
Organizations analyze customers’ personal data to understand and model their behavior. Identifying customers’ gender is a significant factor in analyzing markets that help plan the promotional campaigns, determine target customers and provide relevant offers. Several techniques were developed to analyze different types of data, including text, image, speech, and biometrics, to identify the gender of ...
Added: October 4, 2022
Pantiukhin D., Речевые технологии 2021 № 3-4 С. 3–16
Added: June 17, 2022
Belov A. V., Sapozhnikov A., Semichasnov I., , in: Proceedings of the 2021 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS).: IEEE, 2021. P. 485–490.
The purpose of this work is to develop algorithms and game mechanics for controlling the car driving along a track using a genetic algorithm for training a neural network with the ability to save and load the obtained weights during training. A genetic algorithm and a neural network were developed using the C ++ programming ...
Added: January 14, 2022
Markvirer V., Sakhipova M., В кн.: Математика и междисциплинарные исследования – 2021.: Пермь: Пермский государственный национальный исследовательский университет, 2021. С. 152–157.
Added: December 19, 2021