Deep Learning-based Data Fusion
Deep Learning-Based Data Fusion is a computational approach within geospatial data fusion that leverages deep neural networks to automatically integrate heterogeneous spatial data sources by learning hierarchical feature representations and their contextual relationships.
527
Publications
32.7K
Citations
2.3K
Authors
800
Institutions
Publications per year
2017–2026
511
Parents
527
Deep learning for pixel-level image fusion: Recent advances and future prospects
Yü Liu, Xun Chen, Zengfu Wang et al. · Information Fusion · 2017 · 725 citations
1–5 of 527
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800
Wuhan University
Wuhan, China
22 h-index
94 publications
8.4K citations

Chinese Academy of Sciences
Beijing, China
21 h-index
73 publications
6.7K citations
China University of Geosciences
Wuhan, China
16 h-index
49 publications
2.2K citations
Aerospace Information Research Institute
Beijing, China
14 h-index
41 publications
3K citations
Tsinghua University
Beijing, China
14 h-index
35 publications
2.8K citations

Xidian University
Xi'an, China
13 h-index
41 publications
2.6K citations
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Cologne, Germany
13 h-index
39 publications
2.4K citations
University of Chinese Academy of Sciences
Beijing, China
13 h-index
30 publications
2.3K citations
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43 publications · 3.2K citations
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45 publications · 2.2K citations
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29 publications · 1.4K citations
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14 publications · 2.2K citations
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14 publications · 553 citations
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