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• Содержание выпуска •
• Supercomputing Software and Hardware •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Information Systems in Culture and Education •
• Methods for Optimal Control and Control Theory •
• Mathematical Foundations of Programming •
• Software and Hardware for Distributed Systems and Supercomputers •
Artificial Intelligence, Intelligence Systems, Neural Networks
Responsible for the Section: doctor of technical Sciences Vyacheslav Khachumov.,
candidate of technical Sciences Eugene Kurshev.
On the left: assigned number of the paper, submission date, the number
of A5 pages contained in the paper,
and the reference to the full-text PDF
/r1/pdf.jpg) .
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Article # 27_2017
10
p.
/r2/pdf.jpg)
PDF |
submitted on 05th
Oct 2017 displayed on
website on 01th
Nov
2017 Natalia Vlasova,
Alexey Podobryaev
Automatic noun phrases extraction using preliminary segmentation and
CRF with semantic features
We consider the task of finding the borders of noun
phrases (NP) that are actants of predicates. First, we make a
preliminary segmentation of sentences to fragments that contain NPs.
Second, we use CRF to find the borders of NPs inside the fragments.
Data from the knowledge base and information about named entities
found in the text are used as features for machine learning. We
present the results of our experiment and discuss future work. (in
Russian).
Key words: shallow parsing, automatic information extraction,
named entities, machine learning. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_21-30.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-21-30 |
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Article # 30_2017
15
p.
PDF |
submitted on
21th
Oct 2017 displayed on
website on 04th
Dec
2017 Alexandr Smirnov,
Egor Ivanov
Automatic noun phrases extraction using preliminary segmentation and
CRF with semantic features
The paper describes the method of searching for
objects on aerial photographs using neural networks, as well as an
algorithm that allows postprocessing of data obtained as a result of
the operation of neural networks. The problem of searching for
aircraft in images is considered. (In Russian).
Key words: object detection, neutal networks, aerial photos. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_85-99.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-85-99 |
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Article # 33_2017
15
p.
PDF |
submitted on 01th
Dec 2017 displayed on
website on 25th
Dec
2017 Andrey Mamontov,
Stanislav Rjabinov
On one method of
saving memory when classifying texts
The article investigates the method of memory saving
in tasks of classification of texts by searching for matching parts
of linear polynomials. The algorithm for finding matching parts in
linear polynomials with integer coefficients is given at the
beginning. This algorithm makes it possible to calculate systems of
linear polynomials with integer coefficients more quickly and use
less memory for their storage. The algorithm is then used to find
the matching parts of the linear polynomials that arise when
classifying texts using the Bayesian classifier. We provide
computational experiments that show memory saving. (In Russian).
Key words: text classification, linear polynomials, integers,
Bayes classifier. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_133-147.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-133-147 |
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Article # 36_2017
11
p.
PDF |
submitted on 04th
Dec 2017 displayed on
website on 25th
Dec
2017 Nikolai Abramov,
Vitaly Fralenko
Neural network
data protection system for computer systems
The work is devoted to the neural network protection
against network attacks for computer systems. The methods of
information protection using the neural network approach, the
algorithm of the analysis of network traffic are offered. The
results of software testing are presented. (In Russian).
Key words: information, analysis, system, security,
protection, artificial neural network. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_197-207.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-197-207 |
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Article # 38_2017
12
p.
PDF |
submitted on 01th
Dec 2017 displayed on
website on 25th
Dec
2017 Duy Nguyen,
Mikhail Khacumov
The method of comparing a 3D object model with a 2D image based on
invariant moments
The solution of the comparison problem comes
down to that of optimizing the orientation of the 3D object model in
order to achieve maximum matching of its projection to the presented
image. The closeness measure is the Euclidean distance between
invariant moments of the compared 2D images. In the presented
formulation, the projection of the 3D model is a grayscale image and
the brightness of the pixel is determined by the distance to the
viewing plane. (In Russian).
Key words: 3D object model, range image, projection,
comparison, orientation control, invariant moments. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_209-220.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-209-220 |
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Article # 45_2017
18
p.
PDF |
submitted on 04th
Dec 2017 displayed on
website on 28th
Dec
2017 Aleksandr Buyko,
Andrey Vinogradov
Action recognition on video using recurrent neural networks
In this paper, we consider the application of
computer vision and recurrent neural networks to solve the problem
of identifying and classifying actions on video. The article
describes the approach taken by the authors to analyze video files.
Recurrent
neural networks uses as a classifier. The classifier takes data in a
“bags of words” format that describes low-level actions. The
histograms contained in a “bags of words” are represented by sets of
video file descriptors. Next algorithms are used to search for
descriptors: SIFT, ORB, BRISK, AKAZE. (In Russian).
Key words: computer vision, descriptors, bags of words, deep
learning, recurrent neural networks, long short-term memory
networks, video analysis. |
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article citation |
http://psta.psiras.ru/read/psta2017_4_327-345.pdf |
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DOI |
https://doi.org/10.25209/2079-3316-2017-8-4-327-345 |
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• Supercomputing Software and Hardware •
• Artificial Intelligence, Intelligence Systems, Neural Networks •
• Information Systems in Culture and Education •
• Methods for Optimal Control and Control Theory •
• Mathematical Foundations of Programming •
• Software and Hardware for Distributed Systems and Supercomputers •
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