Арустамян Валентина Александровна

В 2021 году окончила Северо-Кавказский федеральный университет по специальности «Математика и компьютерные науки» с присвоением квалификации «Бакалавр».

С 2021 года – стажер-исследователь отдела Модулярных вычислений и Искусственного интеллекта Северо-Кавказского федерального университета.

В 2023 окончила Северо-Кавказский федеральный университет по специальности «Прикладная
математика и информатика» с присвоением квалификации «Магистр».

Стаж научной деятельности 4 года

Повышение квалификации:

Web-программирование, 2019-2020, Северо-Кавказский федеральный университет

Высокопроизводительные вычисления, цифровая обработка изображений, машинное обучение и искусственный интеллект.

1. R. Abdulkadirov, P. Lyakhov, V. Baboshina, Physics-informed neural network model using natural gradient descent with Dirichlet distribution - ScienceDirect., Engineering Analysis with Boundary Elements, Volume 178, 2025, 106282, ISSN 0955-7997

2. Lyakhov, P., Orazaev, A., Baboshina, V., Odintcov, S., Esaulko, A. (2025). Comparative Analysis of Vegetation Indices on Agricultural Images of Different Modalities | SpringerLink. In: Samoylenko, I., Rajabov, T. (eds) Innovations in Sustainable Agricultural Systems, Agriculture 4.0 and Precision Agriculture, Volume 2. ISAS 2025 2025. Lecture Notes in Networks and Systems, vol 1534. Springer, Cham.

3. P. A. Lyakhov, U. A. Lyakhova, V. A. Baboshina, V. V. Baryshev, N. N. Nagornov, Detection of attention state in children with autism spectrum disorder based on neural network classification of electroencephalograms, Вестн. С.-Петербург. ун-та. Сер. 10. Прикл. матем. Информ. Проц. упр., 2025, том 21, выпуск 1, 92–111

4. Baboshina VA, Lyakhov PA, Lyakhova UA, Pismennyy VA. Bidirectional Encoder representation from Image Transformers for recognizing sunflower diseases from photographs. Computer Optics 2025; 49(3): 435-442. DOI: 10.18287/2412-6179-CO-1514.

5. R. I. Abdulkadirov, P. A. Lyakhov, V. A. Baboshina and N. N. Nagornov, "Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent," in IEEE Access, vol. 12, pp. 168428-168444, 2024, doi: 10.1109/ACCESS.2024.3491614.

6. R. Abdulkadirov, P. Lyakhov, V. Baboshina,  Physics-informed neural network model using natural gradient descent with Dirichlet distribution - ScienceDirect, Engineering Analysis with Boundary Elements, Volume 178, 2025, 106282, ISSN 0955-7997

7. Orazaev A, Lyakhov P, Baboshina V, Kalita D. Neural Network System for Recognizing Images Affected by Random-Valued Impulse Noise. Applied Sciences. 2023; 13(3):1585. 

8. Lyakhov P. A., Lyakhova U. A., Baboshina V. A., Baryshev V. V., Nagornov N. N. Detection of attention state in children with autism spectrum disorder based on neural network classification of electroencephalograms. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2025, vol. 21, iss. 1, pp. 92–111. https://doi.org/10.21638/spbu10.2025.107.

9. Baboshina VA, Orazaev AR, Lyakhov PA, Boyarskaya EE. Neural network recognition system for video transmitted through a binary symmetric channel. Computer Optics 2024; 48(4): 582-591. DOI: 10.18287/2412-6179-CO-1388.

10. Lavrinenko, I., Semenova, N., Baboshina, V. (2023).Interactive Methods in the Study of the Discipline “Mathematics” for Non-mathematical Specialties | SpringerLink. In: Alikhanov, A., Lyakhov, P., Samoylenko, I. (eds) Current Problems in Applied Mathematics and Computer Science and Systems. APAMCS 2022. Lecture Notes in Networks and Systems, vol 702. Springer, Cham. 

11. Zhuravleva, I., Andrukhiv, L., Yartseva, E., Baboshina, V. (2023). Applied Mathematics and Informatics Bachelor's and Master's Educational Programs Continuity During Updating Educational Standards | SpringerLink. In: Alikhanov, A., Lyakhov, P., Samoylenko, I. (eds) Current Problems in Applied Mathematics and Computer Science and Systems. APAMCS 2022. Lecture Notes in Networks and Systems, vol 702. Springer, Cham. 

12. V. A. Baboshina, P. A. Lyakhov and D. I. Kalita, "Comparative Analysis of Despeckle Filtering Methods for Ultrasound Images," 2022 International Conference on Quality Management, Transport and Information Security, Information Technologies (IT&QM&IS), Saint Petersburg, Russian Federation, 2022, pp. 66-71, doi: 10.1109/ITQMIS56172.2022.9976753.

13. P. A. Lyakhov, A. S. Voznesensky, E. D. Shalugin, A. R. Orazaev and V. A. Baboshina, "Bilateral and Median Filter Combination for High-Quality Cleaning of Random Impulse Noise in Images," 2022 11th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro, 2022, pp. 1-5, doi: 10.1109/MECO55406.2022.9797149.

14. V. A. Baboshina, A. R. Orazaev, E. D. Shalugin and A. M. Sinitca, "Combined Use of a Bilateral and Median Filter to Suppress Gaussian Noise in Images," 2022 11th Mediterranean Conference on Embedded Computing (MECO), Budva, Montenegro, 2022, pp. 1-5, doi: 10.1109/MECO55406.2022.9797124.

15. Lyakhov, P.A., Lyakhova, U.A., Baboshina, V.A. (2022). Neural Network Classification of Dermatoscopic Images of Pigmented Skin Lesions | SpringerLink. In: Tchernykh, A., Alikhanov, A., Babenko, M., Samoylenko, I. (eds) Mathematics and its Applications in New Computer Systems. MANCS 2021. Lecture Notes in Networks and Systems, vol 424. Springer, Cham.