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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">bsuir</journal-id><journal-title-group><journal-title xml:lang="ru">Доклады БГУИР</journal-title><trans-title-group xml:lang="en"><trans-title>Doklady BGUIR</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1729-7648</issn><issn pub-type="epub">2708-0382</issn><publisher><publisher-name>БГУИР</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">bsuir-193</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Статьи</subject></subj-group></article-categories><title-group><article-title>РЕШЕНИЕ ЗАДАЧИ РАЗГРАНИЧЕНИЯ ДОСТУПА В СИСТЕМУ НА ОСНОВЕ НЕЙРОННОЙ СЕТИ СВЕРТКИ</article-title><trans-title-group xml:lang="en"><trans-title>A SOLUTION TO SYSTEM ACCESS PROBLEM BASED ON CONVOLUTIONAL NEURAL NETWORK APPROACH</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Искра</surname><given-names>Н. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Iskra</surname><given-names>N. A.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Белорусский государственный университет информатики и радиоэлектроники</institution><country>Belarus</country></aff><pub-date pub-type="collection"><year>2013</year></pub-date><pub-date pub-type="epub"><day>03</day><month>06</month><year>2019</year></pub-date><volume>0</volume><issue>4</issue><fpage>74</fpage><lpage>78</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Искра Н.А., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Искра Н.А.</copyright-holder><copyright-holder xml:lang="en">Iskra N.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://doklady.bsuir.by/jour/article/view/193">https://doklady.bsuir.by/jour/article/view/193</self-uri><abstract><p>Предлагается алгоритм, в основе которого лежит извлечение главных компонент изображений в качестве информативных признаков и нейронная сеть свертки в качестве классификатора. Эксперименты показывают частичную инвариантность к поворотам, масштабированию и деформациям, что достигается благодаря иерархическому извлечению информативных признаков. Доля правильного распознавания образов лиц составила 99 %.</p></abstract><trans-abstract xml:lang="en"><p>The algorithm based on the principal components of the images as informative features extracting and convolutional neural network as a classifier is proposed. Experiments have shown partial invariance to the rotation, scaling and deformation, achieved through a hierarchical extraction of informative features. The resulting percentage of correct recognition rate of persons is up to 99%.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>нейронная сеть свертки</kwd><kwd>анализ главных компонент</kwd><kwd>идентификация личности</kwd><kwd>биометрия</kwd><kwd>разграничение доступа</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Bryliuk D., Starovoitov V. // Proc. of the 2nd International Conference on Artificial Intelligence, Crimea, Ukraine, 2002. P. 428.</mixed-citation><mixed-citation xml:lang="en">Bryliuk D., Starovoitov V. // Proc. of the 2nd International Conference on Artificial Intelligence, Crimea, Ukraine, 2002. P. 428.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Lawrence S., Giles C.L., Tsoi A.C. et. al. 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