Didur, V.Molchanova, M.Mazurets, O.Мазурець, Олександр Вікторович2025-05-292025-05-292025Didur V., Molchanova M., Mazurets O. Research on the effectiveness of neural network detection of plots with the destroyed buildings remains. Modern technologies and science: problems, new and relevant developments. Proceedings XXI International Scientific and Practical Conference. May 26, 2025. Zaragoza, Spain. Pp. 245-251https://elar.khmnu.edu.ua/handle/123456789/18411This paper explores the effectiveness of neural network approaches for detecting and classifying plots containing the remains of destroyed buildings using aerial imagery. The proposed method integrates a YOLO-based object detector and a Vision Transformer for multi-class classification of structural debris such as concrete, metal, brick, and wood. The system achieves high accuracy (97%) and demonstrates strong performance across key classification metrics. This research highlights the critical role of deep learning in accelerating post-disaster damage assessment, supporting emergency response, cultural heritage preservation, and long-term urban resilience planning.enСтаття