Building seismic damage grade classification method based on deep learning
A technology of deep learning and hierarchical classification, applied in the field of hierarchical classification, to achieve the effects of easy access, reduced interference, and reduced manpower and material resources
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[0068]CombineFigure 5 According to the post-earthquake building image data and the post-earthquake building image data collected on the Internet, the post-earthquake building damage level classification method is based on the deep learning of the present invention:
[0069]The first step is specifically: the post-earthquake building image data and the high-resolution post-earthquake building image data of different structures collected from the Internet form image set A. According to the format of the Cityscapes data set, use the Labelme tool to analyze each of the images. Class objects are labeled and named. Produce diversified building image data sets after the earthquake.
[0070]The second step is specifically: applying DeepLabV3+ as the basic image segmentation model, where the resolution of the input image of the input layer is not limited, and pre-training the image segmentation model using the Cityscapes data set to obtain the model MSP . Select the classification you...
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