Spatial Context Modeling
Spatial Context Modeling is a computational framework that formalizes the characterization of spatial dependencies and relational patterns among entities within a defined geographic or geometric space, distinguished by its integration of topological, directional, and distance-based features to enhance representation learning in spatially-referenced data.
81
Publications
5.5K
Citations
266
Authors
116
Institutions
Publications per year
2017–2026
40
81
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
Lukas Hoyer, Dengxin Dai, Haoran Wang et al. · 2023 · 302 citations
1–5 of 81
266
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3
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German Research Centre for Artificial Intelligence, Germany
2 publications · 111 citations
2
h-index
2
h-index
1–5 of 266
116
The University of Texas at San Antonio
San Antonio, United States
4 h-index
4 publications
166 citations
Tsinghua University
Beijing, China
4 h-index
8 publications
396 citations

Chinese Academy of Sciences
Beijing, China
4 h-index
14 publications
663 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
4 publications
247 citations
Wuhan University
Wuhan, China
3 h-index
7 publications
100 citations

Xidian University
Xi'an, China
3 h-index
15 publications
727 citations

Hefei University of Technology
Hefei, China
3 h-index
7 publications
238 citations

University of Waterloo
Waterloo, Canada
3 h-index
9 publications
877 citations
1–8 of 116
6 publications · 312 citations
6
h-index
3 publications · 133 citations
3
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Conference · 3 publications · 269 citations
3
h-index
3 publications · 155 citations
3
h-index
1 publications · 29 citations
2
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1–5