Datalogic structure for intelligent system for areas localization in photos with the remains of buildings using neural network

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dc.contributor.authorDydo, R.
dc.contributor.authorSobko, O.
dc.contributor.authorKlimenko, V.
dc.contributor.authorMazurets, O.
dc.contributor.authorМазурець, Олександр Вікторович
dc.date.accessioned2025-05-29T15:59:11Z
dc.date.available2025-05-29T15:59:11Z
dc.date.issued2025
dc.description.abstractThis paper presents the development of a datalogic structure for an intelligent system designed to detect and localize areas in photographic images that contain remains of destroyed buildings using neural networks. The system integrates pre-processing, object detection via the YOLO model, and multiclass classification of building materials. A relational database was designed to store and manage information about images, segments, detected materials, experiments, and classification metrics. This structured approach ensures efficient data handling, supports analytical reporting, and enables retraining of models based on historical data, contributing to more accurate and scalable damage assessment solutions in post-conflict or disaster-struck areas.
dc.identifier.citationDydo R., Sobko O., Klimenko V., Mazurets O. Datalogic structure for intelligent system for areas localization in photos with the remains of buildings using neural network. Modern Scientific Research: Theoretical and Practical Aspects. Proceedings II International Scientific and Practical Conference. May 26-28, 2025. Riga, Latvia. Pp. 123-127. URL: https://www.eoss-conf.com/wp-content/uploads/2025/05/Riga_Latvia_26.05.25.pdf
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/18415
dc.language.isoen
dc.titleDatalogic structure for intelligent system for areas localization in photos with the remains of buildings using neural network
dc.typeСтаття
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