dc.contributor.author | Прус, Б. В. | uk |
dc.contributor.author | Ракитянська, Г. Б. | uk |
dc.date.accessioned | 2025-08-19T07:56:16Z | |
dc.date.available | 2025-08-19T07:56:16Z | |
dc.date.issued | 2025 | |
dc.identifier.citation | | uk |
dc.identifier.uri | https://ir.lib.vntu.edu.ua//handle/123456789/48696 | |
dc.description.abstract | Розглянуто задачу класифікації сцен на мобільних пристроях з використанням трансферного навчання. | uk |
dc.description.abstract | The problem of scene classification on mobile devices using transfer learning is considered. A method of distilling knowledge from deep neural networks into fuzzy classifiers is proposed, which allows for effective determination of visible relationships between objects at low computational costs. | en |
dc.language.iso | uk_UA | uk_UA |
dc.publisher | ВНТУ | uk |
dc.relation.ispartof | // Матеріали LIV Всеукраїнської науково-технічної конференції підрозділів ВНТУ, Вінниця, 24-27 березня 2025 р. | uk |
dc.relation.uri | https://conferences.vntu.edu.ua/index.php/all-fitki/all-fitki-2025/paper/view/23682 | |
dc.subject | класифікація сцени | uk |
dc.subject | виявлення об’єктів | uk |
dc.subject | визначення візуальних зв’язків | uk |
dc.subject | дистиляціязнань | uk |
dc.subject | гранульований нечіткий класифікатор на основі прототипу | uk |
dc.subject | scene classification | uk |
dc.subject | object detection | uk |
dc.subject | visual relationship detection | uk |
dc.subject | knowledge distillation | uk |
dc.subject | prototype-based granular fuzzy classifier | uk |
dc.title | Моделі та методи трансферного навчання для обробки зображень сцен на мобільних пристроях | uk |
dc.type | Thesis | |
dc.identifier.udc | 004.8 | |
dc.relation.references | Duda R.O., Hart P.E. (1973) Pattern Classification and Scene Analysis. John Wiley & Sons, Hoboken. | |
dc.relation.references | H. Li, G. Zhu, L. Zhang, Y. Jiang, Y. Dang, H. Hou, P. Shen, X. Zhao, S. A. Ali Shah, M. Bennamoun, Scene Graph Generation: A comprehensive survey, Neurocomputing, Vol. 566, 2024, 127052, https://doi.org/10.1016/j.neucom.2023.127052. | |
dc.relation.references | L. Xie, F. Lee, L. Liu, K. Kotani, Q. Chen. Scene recognition: A comprehensive survey, Pattern Recognition, Volume 102, 2020, 107205, https://doi.org/10.1016/j.patcog.2020.107205. | |
dc.relation.references | X. Wang, Z. Zhu, Context understanding in computer vision: A survey. Computer Vision and Image Understanding, Volume 229, 2023, 103646, https://doi.org/10.1016/j.cviu.2023.103646. | |
dc.relation.references | V. Kamath, A. Renuka, Deep learning-based object detection for resource constrained devices: Systematic review, future trends and challenges ahead, Neurocomputing, Vol. 531, 2023, P. 34-60, https://doi.org/10.1016/j.neucom.2023.02.006. | |
dc.relation.references | Pedrycz W. Granular Computing: Analysis and Design of Intelligent Systems. CRC Press, Bosa Roca (2018) https://doi.org/10.1201/9781315216737 | |
dc.relation.references | Yao Y. Three-way decision and granular computing, International Journal of Approximate Reasoning, Vol. 103, 2018, P. 107-123, https://doi.org/10.1016/j.ijar.2018.09.005. | |
dc.relation.references | Rotshtein A., Rakytyanska H. Fuzzy Evidence in Identification, Forecasting and Diagnosis, vol. 275. Studies in Fuzziness and Soft Computing. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-25786-5 | |
dc.relation.references | Angelov P., Gu X. Deep rule-based classifier with human-level performance and characteristics. Information Sciences. Vol. 463464, P. 196213 (2018). https://doi.org/10.1016/j.ins.018.06.048 | |
dc.relation.references | Rakytyanska H. (2023). Knowledge Distillation in Granular Fuzzy Models by Solving Fuzzy Relation Equations. In: Pedrycz, W., Chen, SM. (eds) Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems. Studies in Computational Intelligence, vol 1100, pp. 95-133. Springer, Cham. https://doi.org/10.1007/978-3-031-32095-8_4 | |
dc.relation.references | Li, H., Zhu, G., Zhang, L., Jiang, Y., Dang, Y., Hou, H., Shen, P., Zhao, X., Ali Shah, S.A., Bennamoun, M.: Scene graph generation: A comprehensive survey. Neurocomputing 566, art. no. 127052 (2024). https://doi.org/10.1016/j.neucom.2023.127052 | |
dc.relation.references | Rakytyanska, H.: Knowledge distillation in granular fuzzy models by solving fuzzy relation equations. In: Pedrycz, W., Chen, S. (eds.) Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems. Studies in Computational Intelligence. vol. 1100, pp. 95133. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-32095-8 4 | |
dc.relation.references | Peeva, K., Kyosev, Y.: Fuzzy Relational Calculus. Theory, Applications and Software. World Scientific, New York (2004) | |
dc.relation.references | Rakytyanska, H.: Inverse inference based on interpretable constrained solutions of fuzzy relational equations with extended maxmin composition. Soft Computing 28, 54615478 (2024). https://doi.org/10.1007/s00500-023-09301-7 | |
dc.relation.references | Rotshtein, A., Rakytyanska, H.: Fuzzy Evidence in Identification, Forecasting and Diagnosis. Studies in Fuzziness and Soft Computing, vol. 275. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-25786-5 | |
dc.relation.references | Rotshtein, A., Rakytyanska, H.: Fuzzy genetic object identification: multipleinputs multiple-outputs case. In: Hippe, Z., Kulikowski, J., Mroczek, T. (eds.) Human-Computer Systems Interaction. Part II. Advances in Intelligent and Soft Computing. vol. 99, pp. 375394. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-23172-8 25 | |
dc.relation.references | Rotshtein, A., Rakytyanska, H.: Fuzzy logic and the least squares method in diagnosis problem solving. In: Sarma, R. (ed.) Genetic Diagnoses. pp. 5397. Nova Science Publishers, New York (2011) | |
dc.relation.references | Rakytyanska, H.: Classification rule hierarchical tuning with linguistic modification based on solving fuzzy relational equations. Eastern-European Journal of Enterprise Technologies 1(4), 5058 (2018). https://doi.org/10.15587/17294061.2018.123567 | |
dc.relation.references | Rakityanskaya, A., Rotshtein, A.: Fuzzy relation-based diagnosis. Automation and Remote Control 68(12), 21982213 (2007). https://doi.org/10.1134/S0005117907120089 | |