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Machine learning in cartography

  • Published:2024-01-02 Issue:1 Volume:51 Page:1-19
  • ISSN:1523-0406
  • Container-title:Cartography and Geographic Information Science
  • language:en
  • Short-container-title:Cartography and Geographic Information Science

Author:

Harrie Lars1ORCID,Touya Guillaume2ORCID,Oucheikh Rachid1ORCID,Ai Tinghua3ORCID,Courtial Azelle2ORCID,Richter Kai-Florian4ORCID

Affiliation:

1. Physical Geography and Ecosystem Science, Lund University, Sweden

2. LASTIG, Univ Gustave Eiffel, IGN-ENSG, France

3. School of Resource and Environmental Sciences, Wuhan University, People’s Republic of China

4. Department of Computing Science, Umeå University, Sweden

Funder

European Research Council

Horizon 2020

Publisher

Informa UK Limited

Reference141 articles.

1. Amini M.R. Feofanov V. Pauletto L. Devijver E. & Maximov Y. (2023). Self-training: A survey. arXiv. http://arxiv.org/abs/2202.12040

2. Bao H. Dong L. Piao S. & Wei F. (2022). BERT pre-training of image transformers arXiv. https://doi.org/10.48550/arXiv.2106.08254

3. A BiLSTM-CNN model for predicting users’ next locations based on geotagged social media

4. A Spatial Adaptive Algorithm Framework for Building Pattern Recognition Using Graph Convolutional Networks

5. A review and conceptual framework of automated map generalization

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reasoning cartographic knowledge in deep learning-based map generalization with explainable AI;International Journal of Geographical Information Science;2024-06-20
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