Ostapchenko, N.Tyschenko, O.Denysenko, B.Mazurets, O.Мазурець, Олександр Вікторович2025-05-292025-05-292025Ostapchenko N., Tyschenko O., Denysenko B., Mazurets O. Semantic search of relevant images using vector databases. Modern Scientific Research: Theoretical and Practical Aspects. Proceedings II International Scientific and Practical Conference. May 26-28, 2025. Riga, Latvia. Pp. 161-165https://elar.khmnu.edu.ua/handle/123456789/18414This paper presents a method for semantic image search using vector databases, enabling efficient retrieval of relevant visual content based on textual or visual queries. The proposed approach leverages state-of-the-art embedding models, such as OpenCLIP, to convert both images and queries into high-dimensional vector representations. These vectors are stored and compared in a vector database to determine semantic similarity. The system supports both text-to-image and image-to-image search, significantly enhancing the precision of results by focusing on content-level meaning rather than keywords. The solution is applicable in various domains requiring fast and accurate access to large-scale image repositories.enСтаття