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This initiative leverages cutting-edge machine learning technique such as Mask R-CNN to automate the identification of buildings in satellite images after disasters. Employing high-resolution Maxar imagery, our models efficiently and accurately pinpoint affected structures, enhancing the speed and effectiveness of emergency responses.
we took nearly 100000 teacher details for training and a small amount of them for testing where we used 1 for least recommended and 5 for most recommended as output for training data.