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The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

A deep learning semantic template matching framework for remote sensing image registration

Li, Liangzhi, Han, Ling, Ding, Mingtao, Cao, Hongye, Hu, Huijuan·2021·ISPRS Journal of Photogrammetry and Remote Sensing
DOI 10.1016/j.isprsjprs.2021.09.012
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  • Machine learning advancements have significantly enhanced the utilization of extensive data to create new topographic datasets based on existing remote sensing sources.

    “In this context, machine learning advancements have significantly enhanced the utilization of extensive data [25] to create new topographic datasets based on existing remote sensing sources [21,[26][27][28][29].”

    From ANADEM: A Digital Terrain Model for South America (2024) · cites this paper as [25]

Citations

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Research works printed but not linked: 44

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Metadata

Authors
Li, L., Han, L., Ding, M., Cao, H., & Hu, H.
Venue
ISPRS Journal of Photogrammetry and Remote Sensing
Publisher
Elsevier BV
Published
2021-11
Volume
181
Pages
205-217
ISSN
0924-2716
DOI
10.1016/j.isprsjprs.2021.09.012
Cited by
67
References
7
Language
en
Licence
Funders
National Natural Science Foundation of China

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