Classification of urban interchange patterns using a model combining shape context descriptor and graph convolutional neural network

IF 4.4 1区地球科学 Q1 REMOTE SENSING

Geo-spatial Information Science Pub Date : 2023-10-31 DOI:10.1080/10095020.2023.2264337

Min Yang, Minjun Cao, Lingya Cheng, Huiping Jiang, Tinghua Ai, Xiongfeng Yan

引用次数: 0

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基于形状上下文描述符和图卷积神经网络的城市立交模式分类

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Geo-spatial Information Science REMOTE SENSING-

CiteScore

10.10

自引率

28.30%

发文量

710

审稿时长

31 weeks

期刊介绍： Geo-spatial Information Science was founded in 1998 by Wuhan University, and is now published in partnership with Taylor & Francis. The journal publishes high quality research on the application and development of surveying and mapping technology, including photogrammetry, remote sensing, geographical information systems, cartography, engineering surveying, GPS, geodesy, geomatics, geophysics, and other related fields. The journal particularly encourages papers on innovative applications and theories in the fields above, or of an interdisciplinary nature. In addition to serving as a source reference and archive of advancements in these disciplines, Geo-spatial Information Science aims to provide a platform for communication between researchers and professionals concerned with the topics above. The editorial committee of the journal consists of 21 professors and research scientists from different regions and countries, such as America, Germany, Switzerland, Austria, Hong Kong and China.