Генерацiя зображень номерних знакiв за допомогою дифузiйної моделi

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dc.contributor.advisorШвай, Надія
dc.contributor.authorШпiр, Марiя
dc.date.accessioned2024-11-04T13:33:14Z
dc.date.available2024-11-04T13:33:14Z
dc.date.issued2024
dc.description.abstractThis thesis addresses the challenges posed by data privacy laws, such as General Data Protection Regulation (GDPR), which limits the availability of datasets necessary for License Plate Recognition (LPR). It introduces a method to generate synthetic license plate images using diffusion models, specifically training a diffusion model on Ukrainian License Plates. These images were analyzed to demonstrate a high success rate in accurately replicating actual license plates. The findings reveal that using these synthetic, pseudo-labeled data as training datasets can increase LPR accuracy by 3% over traditional methods, showing the potential of diffusion models to produce realistic synthetic data for LPR applications, therefore avoiding the limitations set forth in the privacy regulations. uk_UA
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/32167
dc.language.isouk uk_UA
dc.statusfirst published uk_UA
dc.subjectdiffusion models uk_UA
dc.subjectsynthetic data uk_UA
dc.subjectlicense plate recognition uk_UA
dc.subjectGDPR uk_UA
dc.subjectprivacy regulations uk_UA
dc.subjectбакалаврська робота uk_UA
dc.titleГенерацiя зображень номерних знакiв за допомогою дифузiйної моделi uk_UA
dc.typeOther uk_UA
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