Decision-theoretic Sensing
Decision-Theoretic Sensing is a computational framework within active perception that formally models sensor deployment and data acquisition as an optimal decision-making process under uncertainty, distinguishing itself by integrating probabilistic beliefs, action outcomes, and utility maximization to guide sensing strategies.
20
Publications
1.1K
Citations
53
Authors
25
Institutions
Publications per year
2017–2026
1
Parents
20
1–5 of 20
53
2
h-index
University at Buffalo, State University of New York, United States
1 publications · 40 citations
1
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1
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1
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Korea Advanced Institute of Science and Technology, South Korea
1 publications · 15 citations
1
h-index
1–5 of 53
25
Duke University
Durham, United States
2 h-index
6 publications
378 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
136 citations

Cornell University
Ithaca, United States
1 h-index
2 publications
436 citations

Zhongyuan University of Technology
Zhengzhou, China
1 h-index
1 publications
33 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
1 publications
19 citations
University of Lausanne
Lausanne, Switzerland
1 h-index
3 publications
60 citations
Lockheed Martin (United States)
Bethesda, United States
1 h-index
1 publications
47 citations
The Ohio State University
Columbus, United States
1 h-index
1 publications
35 citations
1–8 of 25
2 publications · 123 citations
2
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1 publications · 26 citations
1
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1 publications · 48 citations
1
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1 publications · 15 citations
1
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1 publications · 60 citations
1
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1–5