GitHub / kushanavbhuyan / Building-Identification-for-Exp-Vul-Risk-Assessment

Information about buildings is, sufficed to say, a very important aspect not just for urban land registry or transportation but also for disaster/hazard risk assessment. Specifically, typological attributes of buildings like number of residents living in them, number of floors, and many more. The study aims at figuring and capturing the typological attributes of the buildings by incorporating deep learning and other proxy information as a means of detecting and characterising the buildings.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kushanavbhuyan%2FBuilding-Identification-for-Exp-Vul-Risk-Assessment

Topics: building, charactersiation, detection, elements-at-risk, encoder-decoder-model, fcn, resnet-50, resunet-architecture, semantic-segmentation, tensorflow2, unet-image-segmentation

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