Probability Density Maps
Probability Density Maps is a spatial uncertainty visualization method that represents the likelihood of occurrence or presence of a phenomenon across geographic space by encoding probability density values within a continuous surface map.
250
Publications
18.9K
Citations
999
Authors
438
Institutions
Publications per year
2017–2026
79
Variants
Probability Density Map
250
GTM: The Generative Topographic Mapping
Chris Bishop, Markus Svensén, Christopher K. I. Williams · Neural Computation · 1998 · 1.4K citations
DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation
Hao Chen, Xiaojuan Qi, Lequan Yu et al. · 2016 · 552 citations
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Centre National de la Recherche Scientifique
Paris, France
7 h-index
24 publications
1.6K citations
Heinrich Heine University Düsseldorf
Düsseldorf, Germany
5 h-index
13 publications
3.2K citations

Malmö University
Malmo, Sweden
5 h-index
7 publications
863 citations
ETH Zurich
Zurich, Switzerland
4 h-index
11 publications
374 citations
University College London
London, United Kingdom
4 h-index
30 publications
1.6K citations
National Tsing Hua University
Hsinchu, Taiwan
4 h-index
4 publications
105 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
4 h-index
17 publications
741 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
3 h-index
7 publications
661 citations
1–8 of 438
Repository · 9 publications · 857 citations
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6 publications · 763 citations
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5 publications · 296 citations
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3 publications · 126 citations
3
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2 publications · 158 citations
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