Oybek Djuraev

Tashkent University of Information Technology

Papers

Total Citations

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About

Oybek Djuraev is a researcher whose work sits at the intersection of computer vision and natural language processing, with a particular focus on text recognition for low-resource languages. His most-cited paper, "Robust Text Recognition for Uzbek Language in Natural Scene Images" (2019, 9 citations), tackles the challenging task of extracting semantic information from text embedded in real-world images—a critical capability for applications ranging from robot navigation to information retrieval and assistive technology for the visually impaired. By addressing the unique orthographic and morphological complexities of the Uzbek language, Djuraev's contributions help bridge a significant gap in scene text recognition, an area long dominated by high-resource languages. His work underscores the importance of developing robust, language-specific models that can operate effectively in diverse, unconstrained environments. As text in natural scenes continues to grow as a source of actionable data, Djuraev's research provides a foundational step toward more inclusive and practical computer vision systems, making him a notable figure in the advancement of multilingual scene understanding.