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Документ Effectiveness research of using ViT neural network architecture for classifying the destroyed buildings remains(2025) Hladun, O.V.; Molchanova, M.O.; Zalutska, O.O.; Mazurets, O.V.; Мазурець, Олександр ВікторовичThis study explores the effectiveness of the Vision Transformer (ViT) neural network for classifying remains of destroyed buildings in post-disaster environments. A software system was developed to preprocess images, train ViT and MobileNetV3 models, and integrate them into a user-friendly application. The models, trained on real-world construction debris images from robotic systems, showed high classification accuracy. Results confirm the ViT model’s potential for reliable, automated damage assessment, supporting faster and safer disaster response.