Bayesian Count Estimation
Bayesian Count Estimation is a statistical inference method that belongs to the class of Bayesian estimation techniques and is distinguished by its use of prior probability distributions to update the uncertainty about an unknown count parameter based on observed data through Bayes' theorem.
34
Publications
2.5K
Citations
93
Authors
57
Institutions
Publications per year
2017–2026
10
Parents
34
Bayesian Loss for Crowd Count Estimation With Point Supervision
Zhiheng Ma, Xing Wei, Xiaopeng Hong et al. · 2019 · 580 citations
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NSF National Center for Atmospheric Research, United States
2 publications · 428 citations
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2
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1–5 of 93
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Duke University
Durham, United States
2 h-index
2 publications
428 citations

Southwest Jiaotong University
Chengdu, China
2 h-index
6 publications
111 citations

University of Minnesota
Minneapolis, United States
2 h-index
4 publications
90 citations
Decision Sciences (United States)
Fort Walton Beach, United States
2 h-index
2 publications
428 citations

NSF National Center for Atmospheric Research
Boulder, United States
2 h-index
2 publications
428 citations
Universidade de São Paulo
São Paulo, Brazil
2 h-index
5 publications
78 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
4 publications
236 citations

University of York
York, United Kingdom
1 h-index
1 publications
36 citations
1–8 of 57
2 publications · 77 citations
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TRR · 2 publications · 45 citations
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2 publications · 78 citations
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2 publications · 428 citations
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1 publications · 18 citations
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