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Детектирование эмоций в мультимедиа контенте
С. 852–857.
А. С. Попова, А. Г. Рассадин, А. А. Пономаренко
In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. The computational experiment was done based on Radvess open dataset including 8 different emotions: "neutral", "calm", "happy," "sad," "angry," "scared", "disgust", "surprised". The best accuracy result was 64%, which was produced by a combination of “|spectrogram + convolution neural network VGG-11”
Konstantinov A., Elizarova Anastasiya P., Utkin L., Computing, Telecommunications and Control 2026 Vol. 19 No. 1 P. 16–25
Decision trees and their ensemble extensions, such as random forests, are widely used as classification models due to their simplicity and interpretability. However, in many real-world tasks where class labels overlap in the feature space, standard decision trees rely on hard splits that create fragile decision boundaries. In these regions, small perturbations in the input ...
Added: October 2, 2026
Zheltyakova M., Korotkov A., Bursov K. et al., Herald of the Russian Academy of Sciences 2026 Vol. 95 No. 6 P. 1048–1057
The Reading the Mind in the Eyes Test (RMET) is a widely used tool for assessing affective mentalization in both clinical and research contexts. Although translated into many languages, no validated Russian-language version has been available. Furthermore, the limited number of stimuli in the original RMET constrains its applicability in neuroimaging studies. This study presents ...
Added: September 13, 2026
Lebedev O. B., Черкасов Р. И., Известия ЮФУ. Технические науки 2025 № 5(247) С. 254–276
This paper considers the application of artificial intelligence technologies, in particular computer vision, in visual information processing systems. A comprehensive analysis of neural network approaches to solving computer vision problems is carried out, including systematization of key types of problems: image classification, object detection and semantic segmentation. The architectural principles of convolutional neural networks are ...
Added: September 10, 2026
Сысоева И. А., Sysoeva T., Новые психологические исследования 2026 № 3 С. 95–114
Currently, instant text messaging is widespread and often replaces regular offline communication. At the same time, such an important component of interaction as understanding the emotions of the interlocutor in online text communication may be difficult because of the lack of nonverbal emotional cues (facial expressions, gestures, etc.). Although it is generally believed that emotional ...
Added: June 22, 2026
Gavrilova E., Novoselova K., Myachykov A. et al., RESEARCH IN AUTISM 2026 Vol. 132 Article 202833
Background
Body movements convey crucial insights into emotions. Although autistic individuals may process these cues differently, the specific factors influencing emotion-from-motion perception in autism remain poorly understood. This systematic review synthesizes current research and highlights key findings in this area of study.
Objectives
This systematic review aimed to assess autistic individuals’ ability to recognize emotions through biological motion (operationalized via ...
Added: April 14, 2026
Бестолкова Г. В., Вестник Донецкого национального университета. Филология и психология 2025 № 6 С. 62–73
The research paper objective is to formulate and integrate the term “langues d’oïl” into contemporary
Russian Romance studies’ conceptual framework in order to expand Romance languages’ scientific knowledge.
In accordance with this goal, the given paper involves a number of objectives: term “langues d’oïl” formation’s
historical background analysis; regional languages’ area description in modern France; comprehensive description
of “French ...
Added: February 23, 2026
Бестолкова Г. В., Теория языка и межкультурная коммуникация 2023 № 3(50) С. 1–15
Significant role in modern Occitan language’s development is played by variety of dialects, subdialects and colloquial speech, that determines relevance of the study undertaken in this article. Occitan language dialects’ number is large, therefore only its northern dialects are considered in detail within this article. The material contained in the article allows to form a ...
Added: February 15, 2026
Kotov F., Timokhin I., Ivanov F., , in: 2023 XVIII International Symposium Problems of Redundancy in Information and Control Systems (REDUNDANCY).: IEEE, 2023.
The Successive Cancellation List (SCL) algorithm is a widely used decoding technique in communication systems. However, constructing the critical set for SCL decoding is a challenging task, as it requires a large number of computations and can lead to significant decoding delays. In this paper, a new approach to critical set construction for SCL decoding ...
Added: January 26, 2026
Nastina E., Sokolov B., / Series OSF "SocArXiv". 2025.
We argue that a classification-based approach to measuring cultural differences across countries or subnational regions is a promising complement, and sometimes an alternative, to the widely used dimensional method in cross-cultural research. The latter summarises cultural variation using continuous dimensions, for example, Hofstede’s famous individualism-collectivism dimension. However, this approach relies on strong parametric assumptions, which are ...
Added: December 23, 2025
Pikul A. S., Безопасность информационных технологий 2024 Т. 31 № 4 С. 116–127
This article explores the potential use of modern computer vision architectures for the task of deepfake detection. The following architectures are considered: EfficientNet, Vision Transformer (ViT), VisionLSTM (ViL), Vision KAN, and Mamba Vision. The novelty of the approach lies in the application and comparison of these architectures, as well as their combination into paired ensembles ...
Added: December 12, 2025
Seleznev L. E., Chupakhin A. A., Kostenko V. A. et al., Optical Memory and Neural Networks (Information Optics) 2023 Vol. 32 No. 2 P. 73–85
We analyze a classification problem of mentally pronounced Russian phonemes based on data obtained by means of an electroencephalography device. We describe the data collection method as well as the methods of the obtained data processing. To solve the small sample size problem we present the augmentation techniques that use the time stretching and the ...
Added: October 2, 2025
Zabolotniy A., Chan R. W., Moiseeva V. et al., Frontiers in Neuroscience 2025 Vol. 19 Article 1623380
We demonstrated the feasibility of finger movement decoding with a tailored Convolutional Neural Network. The performance of our approach was comparable to complex deep learning architectures, while providing faster and interpretable outcome. This algorithmic strategy holds high potential for the investigation of the mechanisms underlying non-invasive neurophysiological recordings in cognitive neuroscience. ...
Added: October 2, 2025
Cham: Springer, 2025.
This book constitutes the refereed proceedings of 34th International Workshops which were held in conjunction with the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025.
The 20 full papers and 8 abstracts included in this workshop volume were carefully reviewed and selected from 42 submissions. ...
Added: September 29, 2025
Artem B., Andreasyan A., Konovalov D. et al., Scientific Reports 2025 Vol. 15 Article 23119
G-quadruplexes (GQs) are non-canonical DNA structures encoded by G-flipons with potential roles in gene regulation and chromatin structure. Here, we explore the role of G-flipons in tissue specification. We present a deep learning-based framework for the genome-wide G-flipon predictions across 14 human tissue types. The model was trained using high-confidence experimental maps of GQ-forming sequences ...
Added: August 8, 2025
Shaitan A., Qi R., Liu S. et al., Science China Information Sciences 2025 Vol. 68 No. 7 Article 170102
Artificial intelligence (AI) is revolutionizing the field of drug development, particularly in addressing key challenges such as drug response prediction, drug combination design, drug repositioning, and drug molecule generation. Traditional drug discovery is hindered by long timelines, high costs, and low success rates, necessitating innovative technologies to accelerate the process. AI technologies, such as deep ...
Added: June 25, 2025