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Распознавание и идентификация лиц на документах
Гл. 9. С. 63–69.
Vnukov A., Райтер М. И.
In this study, the possibility of identifying a person according to the main characteristic features is considered. The goal of the work is to realize the knowledge gained about existing algorithms for creating software that recognizes and identifies the person on the image. In the course of the work, the existing algorithms of face recognition and identification were considered, the most suitable ones 69 were selected and implemented, information was received on their speed and accuracy. The result of the work can be supplemented and modified in the future.
De Gruyter, 2023.
Algebraic geometrical properties of functions defined by integral transformations are studied ...
Added: October 31, 2025
Яцкин Д. В., Калинов И. А., В кн.: Перспективные системы и задачи управления: материалы Двенадцатой Всероссийской научно-практической конференции и Восьмой молодежной школы-семинара «Управление и обработка информации в технических системах».: Ростов н/Д: Издательство Южного федерального университета, 2017. С. 531–536.
В работе приведены и описаны модели методы и алгоритмы патрулирования пространства на примере задачи обнаружении человеческого лица на заранее известной территории роевой группой мультироторов. Работа описанных алгоритмов была подтверждена многочисленными экспериментами, на их основании были сделаны выводы об эффективности и границах применимости тех или иных подходов. ...
Added: March 7, 2025
Savchenko A., Maslov D., Makarov I., , in: ECAI 2024. 27th European Conference on Artificial Intelligence, October 19 – 24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024).: IOS Press, 2024. P. 4439–4442.
Added: February 15, 2025
Baulina M., Kosonogov V., Frontiers in Psychology 2024 Vol. 14 Article 1218124
Developmental dyscalculia (DD) is a subtype of learning disabilities, which is characterized by lower mathematical skills despite average intelligence and average or satisfactory performance in other academic areas. It is not fully understood how such deficits emerge in the course of brain development. When considering the mechanisms of dyscalculia, two domain-specific systems are distinguished. The ...
Added: November 13, 2023
Churaev E., Savchenko A., Компьютерная оптика 2023 Т. 47 № 5 С. 806–815
In this paper, an approach that can significantly increase the accuracy of facial emotion recogni- tion by adapting the model to the emotions of a particular user (e.g., smartphone owner) is consid- ered. At the first stage, a neural network model, which was previously trained to recognize facial expressions in static photos, is used to ...
Added: May 18, 2023
Alexandrov D., Программная инженерия 2022 Vol. 13 No. 7 P. 331–343
Trends in computer vision and pattern recognition and capabilities of modern computers contributed to a consid- erable amount of research of these areas application in facial recognition systems. The purpose of this paper is to investigate the most significant methods of face recognition. In the first two sections of current paper, the methods of face ...
Added: October 31, 2022
Соколова А. Д., Savchenko A., Nikolenko S. I., Компьютерная оптика 2022 Т. 46 № 5 С. 801–807
Одной из основных проблем современных нейросетевых дескрипторов в задаче идентификации лиц является малое число обучающих примеров определенного типа: изображения плохого качества, разный масштаб или освещение, лица детей, пожилых людей, редкие расы. В результате точность распознавания оказывается низкой для входных изображений, не похожих на большинство изображений в наборе данных, используемом для настройки метода извлечения признаков. В ...
Added: September 29, 2022
Markvirer V., Ulitina S., , in: Development of Science = Развитие науки : материалы конкурса исследовательских работ на английском языке (2020–2021 г.).: ПГКУБ им. А. М. Горького, 2021. P. 66–72.
The article presents analytical review of existed solutions and technologies applied in computer vision control access systems, video monitoring and analysis areas. Such technologies are parts of the smart city concept and commonly used for recognition of faces in modern office buildings and business centers. Face recognition is used to distinct employees and guests, separated ...
Added: September 20, 2021
Kharchevnikova A., Savchenko A., PeerJ Computer Science 2021 Vol. 7:e391 P. 1–18
The article is considering the problem of increasing the performance and accuracy of video face identification. We examine the selection of the several best video frames using various techniques for assessing the quality of images. In contrast to traditional methods with estimation of image brightness/contrast, we propose to utilize the deep learning techniques that estimate ...
Added: February 25, 2021
Salikhov D., Симонова С. В., Муниципальное имущество: экономика, право, управление 2020 № 3 С. 23–27
С развитием технологий и городской инфраструктуры возникает необходимость цифровизации традиционных задач обеспечения безопасности, правопорядка, поиска лиц, находящихся в розыске, контроля за перемещением граждан, в отношении которых в установленном порядке введены определенные ограничения, и пр. Технологически на подоб- ные запросы есть цифровые решения и (или) принципиальная возможность их внедрения. Однако вопрос правовых условий и предпосылок для ...
Added: February 23, 2021
Savchenko A., Записки научных семинаров ПОМИ РАН 2021 Т. 499 С. 267–283
In this paper fast image recognition techniques based on statistical sequential analysis are discussed. We examine the possibility to sequentially process the principal components and organize a convolutional neural net- work with early exits. Particular attention is paid to sequentially learn multi-task lightweight neural network model to predict several facial at- tributes (age, gender and ...
Added: January 27, 2021
Ahmed Munna M. T., International Journal of Engineering and Technology 2018 Vol. 7 No. 4 P. 3990–3994
Darkness is the inverse state of the brightness, is obtained as an absence of noticeable light and illumination. Generally, face detection applications cannot detect any human face in a dark image, where the image has captured from the dark environment or dark night. In this manuscript, we demonstrate our experiment, where we use Contrast Stretching, ...
Added: October 29, 2019
Sokolova A., Savchenko A., Optical Memory and Neural Networks (Information Optics) 2020 Vol. 29 No. 1 P. 19–29
The goal of the study is to increase the computation efficiency of the face recognition that uses feature vectors to describe facial images on photos and videos. These high-dimensional feature vectors are nowadays produced by convolutional neural networks. The methods to aggregate the features generated for each video frame are used to process the video ...
Added: October 25, 2019
Savchenko A., PeerJ Computer Science 2019 Vol. 5:e197 P. 1–26
This paper is focused on the automatic extraction of persons and their attributes (gender, year of born) from album of photos and videos. A two-stage approach is proposed in which, firstly, the convolutional neural network simultaneously predicts age/gender from all photos and additionally extracts facial representations suitable for face identification. Here the MobileNet is modified ...
Added: June 12, 2019
Tarasov Alexander V., Savchenko A., , in: Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer ScienceVol. 11179.: Berlin: Springer, 2018. Ch. 19 P. 191–198.
In this paper we address the group-level emotion classification problem in video analytic systems.We propose to apply the MTCNN face detector to obtain facial regions on each video frame. Next, off-the-shelf image features are extracted from each located face using preliminary trained convolutional neural networks. The features of the whole frame are computed as a ...
Added: December 12, 2018
Savchenko A., , in: Proceedings of the 24th International Conference on Pattern Recognition (ICPR).: IEEE, 2018. P. 3262–3267.
In this paper we deal with unconstrained face recognition with few training samples. The facial images are described with the off-the shelf high-dimensional features extracted with a deep convolutional neural network (CNN), which was preliminarily trained with an external very-large dataset. We focus on drawbacks of conventional probabilistic neural network (PNN), namely, low recognition performance ...
Added: December 2, 2018
Samonenko I., Интеллектуальные системы в производстве 2003 Т. 2 С. 167–170
Added: September 28, 2018
Samonenko I., Волченков М. П., Интеллектуальные системы. Теория и приложения 2005 Т. 9 С. 153–157
Added: September 28, 2018
Savchenko A., , in: Proceedings of the IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI 2018).: IEEE, 2018. P. 515–520.
This paper is focused on still-to-video face recog- nition with large number of subjects based on computation of distances between high-dimensional embeddings extracted using deep convolution neural networks. We propose to utilize granular structures and sequentially process granular representations of all frames of the input video. The coarse-grained granules include only low number of the ...
Added: September 17, 2018
Zinchenko O., Yaple Z., Arsalidou M., Frontiers in Human Neuroscience 2018 Vol. 12 P. 1–9
Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic ...
Added: June 15, 2018
Savchenko A., Belova N. S., Expert Systems with Applications 2018 Vol. 108 P. 170–182
The paper deals with unconstrained face recognition task for the small sample size problem based on computation of distances between high-dimensional off-the-shelf features extracted by deep convolution neural network. We present the novel statistical recognition method, which maximizes the likelihood (joint probabilistic density) of the distances to all reference images from the gallery set. This ...
Added: May 17, 2018
Соколова А. Д., Savchenko A., В кн.: Материалы XXIII международной научно-технической конференции «Информационные системы и технологии-2017».: [б.и.], 2017. С. 870–875.
Рассматривается задача структурирования информации в программных системах видеонаблюдения с помощью группирования видеоданных, в которых присутствуют идентичные лица. Сделан акцент на эффективную кластеризацию видеопоследовательностей с использованием сверточных нейронных сетей для извлечения характерных признаков. Разработан новый алгоритм кластеризации фрагментов видео на основе технологий глубокого обучения и статистического подхода. Приведены предварительные результаты экспериментального исследования точности и быстродействия предложенного ...
Added: October 24, 2017
Savchenko A., Компьютерная оптика 2017 Т. 41 № 3 С. 422–430
In this paper we focus on the image recognition problem in the case of small sample size based on the nearest neighbor rule and matching of high-dimensional feature vectors extracted with the deep convolutional neural network. We propose the novel recognition algorithm based on the maximum likelihood method for the joint density of dissimilarities between ...
Added: July 8, 2017