Перегляд за Автор "Denysenko, B."

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  • Ескіз
    Документ
    Semantic search of relevant images using vector databases
    (2025) Ostapchenko, N.; Tyschenko, O.; Denysenko, B.; Mazurets, O.; Мазурець, Олександр Вікторович
    This 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.
  • Ескіз
    Документ
    Software architecture of information system for exchanging LLM thematic prompts
    (2025) Denysenko, B.; Shevchuk, P.; Molchanova M.; Mazurets, O.; Мазурець, Олександр Вікторович
    The article presents the design of a software architecture for an information system focused on the exchange of thematic prompts for large language models. As the use of LLMs grows across various domains, the need for a structured platform to manage, share, and evaluate prompts becomes critical for productivity, reproducibility, and collaboration. The system is based on the MVC architectural pattern (Laravel framework) and includes key modules for authentication, prompt management, subscription/payment handling, and administration. The proposed solution enables role-based access, prompt versioning, user feedback, and integration with LLM APIs, laying the foundation for scalable, collaborative, and transparent prompt engineering