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A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model
In this research, we have carefully accumulated a relatively challenging dataset that contains images collected from various sources for three different disasters: fire, water and land.
Deep-learning coupled with novel classification method to classify the urban environment of the developing world
Image encompassing 70% of the urban space was used for training and the remaining 30% was used for testing and validation.
LULC Segmentation of RGB Satellite Image Using FCN-8
This work presents use of Fully Convolutional Network (FCN-8) for semantic segmentation of high-resolution RGB earth surface satel-lite images into land use land cover (LULC) categories.
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