用可解释的人工智能推理基于深度学习的地图泛化中的制图知识

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-06-20 DOI:10.1080/13658816.2024.2369535

Cheng Fu, Zhiyong Zhou, Yanan Xin, Robert Weibel

引用次数: 0

摘要

制图地图泛化涉及复杂的规则，尽管过去几十年来付出了很多努力，但仍未实现完全自动化。开创性的研究表明，一些地图基因...

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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Reasoning cartographic knowledge in deep learning-based map generalization with explainable AI

Cartographic map generalization involves complex rules, and a full automation has still not been achieved, despite many efforts over the past few decades. Pioneering studies show that some map gene...

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.