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A New Sport Teams Logo Dataset for Detection Tasks
Ch. 8. P. 87–97.
Kuznetsov A., Savchenko A.
In this research we introduce a new labelled SportLogo dataset, that contains images of two kinds of sports: hockey (NHL) and basketball (NBA). This dataset presents several challenges typical for logo detection tasks. A huge number of occlusions and logo view changes during playing games lead to an ambiguity of a straightforward detection approach use. Another issue is logo style changes due to seasonal kits updates. In this paper we propose a two stage approach, in which, firstly, an input image is processed by a specially trained scene recognition convolutional neural network. Second, conventional object detectors are applied only for sport scenes. Experimental study contains results of different combinations of backbone and detector convolutional neural networks. It was shown that MobileNet + YOLO v3 solution provides the best quality results on the designed dataset (mAP = 0.74, Recall = 0.87).
In book
Vol. 12334. , Cham: Springer, 2020.
Vasilev A., Kapitanov A., Roman Solovyev et al., PeerJ Computer Science 2026 Vol. 12 Article 3724
This article introduces MinMAE, a novel activation calibration method for Post-Training Quantization (PTQ) that significantly reduces accuracy loss in Convolutional Neural Networks (CNN). Motivated by the need for high-fidelity quantization without costly retraining, MinMAE directly minimizes the Mean Absolute Error (MAE) between original and dequantized activations, making it robust to outliers that degrade standard methods. ...
Added: May 3, 2026
Shadrina E. V., Мохова В. О., Загоскин В. А. et al., Нижегородский психологический альманах 2024 № 2
The article considers the problem of learning of recognizing emotions from pictures. A review and analysis of domestic and foreign works of scientists dealing with the problem of emotional intelligence was carried out. Its formation, influence on human activity and existing variants of its structure were considered, and common features in the understanding of emotional ...
Added: April 9, 2026
Karpukhin I., Shipilov F., Savchenko A., Neurocomputing 2026 Vol. 672 Article 132771
Forecasting multiple future events within a given time horizon is essential for applications in finance, retail,
social networks, and healthcare. This problem is typically addressed using Marked Temporal Point Processes
(MTPP), which provide a principled framework for modeling both event timing and event labels. While most
existing research focuses on predicting only the next event, forecasting distant future ...
Added: February 25, 2026
Moshkin A., Лапутин Ф. А., Сидоров И. В., DIGITAL DIAGNOSTICS 2024 Т. 5 № S1 С. 40–42
BACKGROUND: Ovarian reserve reflects a woman's ability to successfully realize reproductive function. The assessment of ovarian reserve is an urgent task for clinical practice [1] and is important in scientific research. The use of computerized diagnostic image processing methods can accelerate and facilitate the performance of routine tasks in clinical practice. Their use in retrospective ...
Added: February 21, 2026
Pikul A. S., В кн.: Альманах научных работ молодых ученых университета ИТМО. Материалы Пятьдесят третьей (LIII) научной и учебно-методической конференции Том 1.: СПб.: Университет ИТМО, 2024. С. 338–342.
Предложен новый подход для улучшения распознавания атак презентации на биометрическую систему распознавания лиц с помощью сверточной сети с механизмом внимания. Проверена центральная гипотеза, которая заключалась в том, что с помощью механизма внимания возможно улучшить результаты работы исходной сверточной нейронной сети. В ходе экспериментов гипотеза была подтверждена. Наибольший прирост по качеству был достигнут на наборе данных ...
Added: December 13, 2025
Pikul A. S., Лепендин А. А., Труды молодых ученых Алтайского государственного университета 2023 № 20 С. 190–193
Представлен новый подход для выявления атак презентации на системы распознавания по лицу. Он основан на использовании механизма графового внимания, применяемого к промежуточным картам характеристик изображений лица, вычисленным сверточной сетью ResNet18. Показано, что предложенный подход позволил добиться высокого качества распознавания поддельных изображений при лицевой биометрической верификации, сравнимого с имеющимися в настоящее время альтернативными решениями. ...
Added: December 12, 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
Grigoriy Simakov, Stepanyants V., Martyusheva A., , in: 2025 International Russian Smart Industry Conference (SmartIndustryCon).: Sochi: IEEE, 2025. P. 794–798.
The development of intelligent transportation systems, and intelligent vehicles in particular, requires significant time and effort, with one of the primary phases being the training of the automated driving system. This training can be conducted using real-world annotated data or within a simulation environment. Simulation tools can provide a wide array of traffic scenarios unavailable ...
Added: May 10, 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
, in: Lecture Notes in Electrical EngineeringVol. 489: Applied Physics, System Science and Computers II.: Springer, 2019. P. 87–100.
To give shift in safety protocols, we have employed advanced deep learning algorithms and frameworks to construct an innovative AI model. The designed model detects the usage of personal protective equipment (PPE) by workers in high-risk industries such as construction and manufacturing. We have used Google’s TensorFlow object detection API to modify and train a model for ...
Added: December 30, 2024
Kseniia Prokudina, Mikhail Skriplyonok, Alexander Vostrikov, , in: 2024 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), 20-24 May 2024.: IEEE, 2024. P. 865–869.
Added: November 26, 2024
Derkacheva A., Frost G., Ermokhina K. et al., , in: 2023 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS).: IEEE, 2023. P. 1–4.
Many studies using convolutional neural networks, including in the field of satellite images, are aimed at recognizing clearly defined objects, such as cars or individual trees. Here we present the first results on mapping the growth stage of tundra shrubs, which is a ‘‘fuzzy’’ target for a network: there are no obvious geometric boundaries of ...
Added: March 22, 2023
Saleh H., Saleh S., Nathan Teyou Toure et al., , in: 2021 IEEE Concurrent Processes Architectures and Embedded Systems Virtual Conference (COPA).: IEEE, 2022. Ch. 7 P. 1–6.
The annual number of road deaths is still increasing, especially in less developed and developing countries. Road accidents are the 5th cause of death and the leading reason for death among young people between 5 and 29 years of age in 2030. In this study, a robust solution is implemented by integrating object recognition with ...
Added: October 31, 2022
Savchenko A., , in: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).: IEEE, 2022. P. 2358–2365.
In this paper, we consider the problem of real-time video-based facial emotion analytics, namely, facial expression recognition, prediction of valence and arousal and detection of action unit points. We propose the novel frame-level emotion recognition algorithm by extracting facial features with the single EfficientNet model pre-trained on Affect-Net. The predictions for sequential frames are smoothed ...
Added: August 29, 2022
Belykh M. Vladimirovna, Belov A. Vladimirovich, , in: 2022 International Conference on Interdisciplinary Research in Technology and Management, IRTM 2022 - Proceedings.: IEEE, 2022. P. 1–4.
Added: July 15, 2022