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

Xiaowei Xu; Wei Liu; Ye Tao; Xiaodong Wang; Jilong Wu

doi:10.1117/12.2557268

3 January 2020 A novel classification method of wall in rural housing pictures based on adapnet network

Xiaowei Xu, Wei Liu, Ye Tao, Xiaodong Wang, Jilong Wu

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 113731O (2020) https://doi.org/10.1117/12.2557268
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

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.

Citation Download Citation

Xiaowei Xu, Wei Liu, Ye Tao, Xiaodong Wang, and Jilong Wu "A novel classification method of wall in rural housing pictures based on adapnet network", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113731O (3 January 2020); https://doi.org/10.1117/12.2557268

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KEYWORDS

Convolution

Buildings

Network architectures

Data modeling

Image classification

Image processing

Feature extraction

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