太阳成8722(中国)有限公司-GREEN NO.1

标题: Recognition of building group patterns using graph convolutional network

作者: Zhao, R (Zhao, Rong); Ai, TH (Ai, Tinghua); Yu, WH (Yu, Wenhao); He, YK (He, Yakun); Shen, YL (Shen, Yilang)

来源出版物: CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE DOI: 10.1080/15230406.2020.1757512 提前访问日期: JUN 2020

摘要: Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network based on graph convolutions to automatically identify building group patterns with arbitrary forms. The method first models buildings by a general graph, and then the neural network simultaneously learns the structural information as well as vertex attributes to classify building objects. We apply this method to real building data, and the experimental results show that the proposed method can effectively capture spatial information to make more accurate predictions than traditional methods.

入藏号: WOS:000545514900001

语言: English

文献类型: Article; Early Access

作者关键词: Building groups; pattern recognition; convolutional neural networks; graph convolution; generalization of buildings

地址: [Zhao, Rong; Ai, Tinghua; He, Yakun; Shen, Yilang] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Yu, Wenhao] China Univ Geosci, Fac Informat Engn, Wuhan, Peoples R China.

通讯作者地址: Ai, TH (corresponding author)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: tinghuaai@whu.edu.cn

影响因子：2.429