Classification of buildings images by damage level

dc.contributor.advisorКузьменко, Дмитроuk_UA
dc.contributor.authorКузнецова, Аннаuk_UA
dc.date.accessioned2025-09-09T14:18:51Z
dc.date.available2025-09-09T14:18:51Z
dc.date.issued2025
dc.description.abstractThis course paper focuses on the development of a machine learning model for classifying destroyed buildings based on the type of damage caused. It explores and compares different approaches to model creation and training, using real-life data of buildings in Ukraine that were damaged as a result of Russian military aggression. The study aims to contribute to effective damage estimation and planning for urban reconstruction in the context of the ongoing war in Ukraine.en_US
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/36546
dc.language.isoen_USen_US
dc.statusfirst publisheden_US
dc.subjectImage Classificationen_US
dc.subjectShellingen_US
dc.subjectConvolutional Neural Networken_US
dc.subjectDeep Learningen_US
dc.subjectComputer Visionen_US
dc.subjectterm paperen_US
dc.titleClassification of buildings images by damage levelen_US
dc.typeOtheren_US
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