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

Authors

266

  1. DA
    David A. Clausi

    University of Waterloo, Canada

    3 publications · 313 citations

    3

    h-index

  2. JL
    Jiebo Luo

    University of Rochester, United States

    3 publications · 200 citations

    3

    h-index

  3. LX
    Lingxi Xie

    Huawei Technologies (China), China

    3 publications · 152 citations

    3

    h-index

  4. GM
    Geert-Jan M. Kruijff

    German Research Centre for Artificial Intelligence, Germany

    2 publications · 111 citations

    2

    h-index

  5. AK
    A. K. Qin

    Swinburne University of Technology, Australia

    2 publications · 290 citations

    2

    h-index

1–5 of 266

Venues

  1. IEEE Transactions on Image Processing

    6 publications · 312 citations

    6

    h-index

  2. IEEE Transactions on Multimedia

    3 publications · 133 citations

    3

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 269 citations

    3

    h-index

  4. 3

    h-index

  5. Expert Systems with Applications

    1 publications · 29 citations

    2

    h-index

1–5