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MobileEmotiFace: Efficient Facial Image Representations in Video-Based Emotion Recognition on Mobile Devices
P. 266–274.
In this paper, we address the emotion classification problem in videos using a two-stage approach. At the first stage, deep features are extracted from facial regions detected in each video frame using a MobileNet-based image model. This network has been preliminarily trained to identify the age, gender, and identity of a person, and further fine-tuned on the AffectNet dataset to classify emotions in static images. At the second stage, the features of each frame are aggregated using multiple statistical functions (mean, standard deviation, min, max) into a single MobileEmotiFace descriptor of the whole video. The proposed approach is experimentally studied on the AFEW dataset from the EmotiW 2019 challenge. It was shown that our image mining technique leads to more accurate and much faster decision-making in video-based emotion recognition when compared to conventional feature extractors.
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
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
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
Morozov D., Garipov T., Lyashevskaya O. et al., Journal of Language and Education 2024 Vol. 10 No. 4 P. 71–84
Introduction: Numerous algorithms have been proposed for the task of automatic morpheme segmentation of Russian words. Due to the differences in task formulation and datasets utilized, comparing the quality of these algorithms is challenging. It is unclear whether the errors in the models are due to the ineffectiveness of algorithms themselves or to errors and inconsistencies ...
Added: January 7, 2025
Petrakova A., Лебедева Е. И., Kuzmina Y. et al., Психология. Журнал Высшей школы экономики 2024 Т. 21 № 2 С. 423–431
This article presents a pilot study with the objective to create and test stimulus material, which consists of photographic portraits of adults and children expressing various emotions. The uniqueness of this work is due to the approach to organizing the creation of stimulus material, in which the models demonstrated emotions not according to an established ...
Added: December 26, 2024
Petrakova A., Лебедева Е. И., Anikudimova E., Экспериментальная психология 2024 Т. 17 № 3 С. 4–15
The work is aimed at studying the performance of emotion recognition of people of different sex and age, expressed without specified criteria, in association with «emotional families». The materials of an empirical online research obtained with the help of the crowdsourcing service «Yandex. Toloka», in which 3,590 tes- ters took part. The subjects guessed one ...
Added: December 26, 2024
Teplyakov L., Kaymakov K., Shvets E. et al., SPIE, 2021.
Line detection is an important computer vision task traditionally solved by Hough Transform. With the advance of deep learning, however, trainable approaches to line detection became popular. In this paper we propose a lightweight CNN for line detection with an embedded parameter-free Hough layer, which allows the network neurons to have global strip-like receptive fields. ...
Added: November 5, 2024
Sysoeva T., Айрапетян Е. А., Психологические исследования: электронный научный журнал 2023 Т. 16 № 92 Статья 1
The current study is aimed to investigate the differences in emotion recognition among representatives of Armenian and Russian cultures. A preliminary study demonstrated that Armenians, unlike Russians, tend to control the expression of anger towards in-group members in greater extent. One hypothesis explaining the cultural influence on emotion recognition suggests that expression norms, which require ...
Added: January 29, 2024
Kartasheva A., Технологос 2020 № 2 С. 15–24
The article examines approaches to emotion recognition in intelligent systems from the point of view of methodological grounds. In interdisciplinary research, where it is necessary to combine approaches from different fields, we face terminological uncertainty, since the problem of describing the emotional sphere is solved by different researchers in line with several main approaches.
First, the ...
Added: October 20, 2023
Demidovskij A., Artyom Tugaryov, Aleksei Trutnev et al., Mathematics 2023 Vol. 14 No. 11 Article 3120
Due to industrial demands to handle increasing amounts of training data, lower the cost of computing one model at a time, and lessen the ecological effects of intensive computing resource consumption, the job of speeding the training of deep neural networks becomes exceedingly challenging. Adaptive Online Importance Sampling and IDS are two brand-new methods for ...
Added: September 12, 2023
Savchenko A., Savchenko L., Makarov I., IEEE Access 2023 Vol. 11 P. 65977–65990
This paper addresses the face recognition task for offline mobile applications. Using AutoML techniques, a novel technological framework is proposed to develop a fast neural network-based facial feature extractor for a concrete device. First, the Once-for-All SuperNet is trained on a large facial dataset. Each device is characterized by its lookup table, which contains the ...
Added: August 28, 2023