Author details
Author's Published Works
Scheduled Maintenance on Monday 1/13/2025
Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.
Author details
Showing 1-5 of 5 results
- Sort
Filter Results
Show
Sort By
Results
Comparative Analysis of Image Sonification Algorithms for Assistive Technology of Sensory Substitution
Anastasia S. Butorova;Egor A. Koryukin;Alina A. Kostromina;Elizaveta N. Shikhova;Nadiya M. Khomenko;Aleksandr P. Sergeev
2024 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)
Year: 2024 | Conference Paper |
Sensory substitution devices assist users with visual impairments to perceive their surroundings through sound generated by processing images from a head-mounted camera. To convey information in a user-friendly manner, images must be sonified according to a specific algorithm. The authors tested three different image sonification algorithms on two volunteers in object localization task. The partic...Show More
Development of an Algorithm for Audiovisual Sensory Substitution with YOLO Network Preprocessing to Reduce the User’s Sensory Overload
Egor A. Koryukin;Anastasia S. Butorova;Veniamin S. Bobakov;Aleksandr P. Sergeev
2024 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)
Year: 2024 | Conference Paper |
Research in the field of sensory substitution provides an opportunity for people with visual impairment to experience the world around them. A lot of algorithms are created for this purpose. However, even after a short period of use, the user experiences sensory overload. This study aimed to create an algorithm for visual-auditory sensory substitution with the neural network preprocessing to minim...Show More
Classification of graph topologies by machine learning methods
Veniamin S. Bobakov;Egor A. Koryukin;Anastasia S. Butorova;Aleksandr P. Sergeev
2023 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA)
Year: 2023 | Conference Paper |
Many objects of the real world, both living and man-made, may be described in the terms of graph theory and represented as graph data. One of the tasks of graph data analysis is to classify graph topologies. This work explored the possibilities of machine learning methods, and in particular graph neural networks (GNNs), to classify graphs with different topologies. The aim was to study the robustn...Show More
Mono vs Stereo Modes of Visual-Auditory Sensory Substitution in Spatial Localization Task
Anastasia S. Butorova;Egor A. Koryukin;Nelli I. Nurullina;Veniamin S. Bobakov;Aleksandr P. Sergeev
2023 Fifth International Conference Neurotechnologies and Neurointerfaces (CNN)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Sensory substitution devices (SSDs) provide visually impaired users with a “visual” perception of the environment by transmitting information about the field of view of the head-mounted camera. To increase the effectiveness of SSDs, the visual data should be pre-processed to convey the spatial information about the object in simple and understandable way. In this work, the authors supposed that th...Show More
Computer vision for obtaining retrospective data of urbanized landscape condition
Egor A. Koryukin;Veniamin S. Bobakov;Anastasia S. Butorova;Aleksandr P. Sergeev
2023 IEEE Ural-Siberian Conference on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)
Year: 2023 | Conference Paper |
Retrospective information about the state of the urbanized environment can be obtained by analyzing images located in the Internet. Methods based on artificial intelligence allow recognizing objects of a given class in images, moreover models based on neural networks demonstrate high recognition accuracy. In this paper, a neural network model is proposed based on its own dataset for recognizing ob...Show More
IEEE Account
Purchase Details
Profile Information
Need Help?
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Contact Us
- Help
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Sitemap
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.