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Распознавание кашля с помощью анализа спектрограмм
С. 230–234.
Dvoynikova A.
Dvoynikova A., В кн.: Сборник трудов XI Конгресса молодых учёныхТ. 2.: Университет ИТМО, 2022.
В работе разрабатывается система для автоматического распознавания вовлеченности собеседников по речи дикторов. В качестве аудиальных признаков используются мел- спектрограммы, которые потом подаются на вход сверточной нейронной сети. Для экспериментальных исследований извлекались как узкополосные мел-спектрограммы, так и широкополосные, отличающие шириной полос (разрешающей способностью). Обучение и тестирование системы проходило на данных корпуса RECOLA, который включал в себя ...
Added: April 25, 2026
Manna S., Ghildiyal S., Bhimani K. R., IEEE Access 2020 Article 1
Face recognition (FR) and verification is the immeasurable technology to encounter any criminal activities nowadays. With the remarkable applications extending from criminal ID, security, and observation to amusement sites. This system (recognition of faces) is exceptionally helpful in banks, air terminals, and different associations for screening customers. In deep learning, convolutional neural networks (CNN) have ...
Added: October 14, 2022
Savchenko A., Belova N. S., Expert Systems with Applications 2022 Vol. 207 Article 117885
In this paper, the computational complexity of the probabilistic neural network for the classification of high-dimensional data is improved. At first, the class probability densities are estimated by using only a few principal components of an observed point. The Gaussian–Parzen kernel is replaced by the orthogonal series estimates of class-conditional densities for each principal component using the Fourier series to speed ...
Added: June 29, 2022
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
Savchenko A., , in: Proceedings of International Joint Conference on Neural Networks 2020 (IJCNN 2020).: Piscataway: IEEE, 2020. P. 1–8.
In this paper the problem of high computational complexity of deep convolutional nets in image recognition is considered. An existing framework of adaptive neural networks is extended by appending the separate classifier to intermediate layers. The hierarchical representations of the input image are sequentially analyzed. If the first classifier returns rather high confidence score, the ...
Added: October 15, 2020
A.S. Kharchevnikova, Savchenko A., Optical Memory and Neural Networks (Information Optics) 2018 Vol. 27 No. 4 P. 246–259
The paper considers the use of convolutional neural networks for the concurrent recognition of the gender and age of a person by video records of his face. The emphasis is on the incorporation of the approach into mobile video-recording software. We have investigated the fusion of decisions obtained during the processing of each video frame, ...
Added: November 5, 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
Pantiukhin D., Карелова Е. -., Информационные технологии 2018 Т. 24 № 6 С. 406–413
This research investigates the effects of training sample balancing while solving intrusion classification task with convolution neural network. Using two convolutional neural networks with similar architecture, we conduct comparative analysis of classification task solution quality with and without training sample balancing. Experiments illustrate the efficiency of using training sample balancing in case of significant differences ...
Added: April 14, 2018