A novel classification method of wall in rural housing pictures based on adapnet network

Based on the pictures of rural housing buildings, the characteristics of housing for the poor are studied, and the appearance of wall is classified by the deep learning method. The degree of poverty is determined by the classification of wall characteristics. Using the transfer learning method, the ResNet101 network is combined with the AdaptNet network to train the house image set. The house pictures are classified using the trained model. Experiments show that the classification accuracy in the recognition of wooden walls and tile walls is improved.

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