Data-driven Range Estimation
Data-Driven Range Estimation is a methodological approach within range estimation that fundamentally relies on empirical data and statistical learning techniques to infer or predict range values, distinguishing itself from model-based or physics-driven approaches by prioritizing observed data patterns over theoretical assumptions.
14
Publications
732
Citations
28
Authors
20
Institutions
Publications per year
2017–2026
3
Parents
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1–5 of 14
28
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University of Genoa
Genoa, Italy
2 h-index
8 publications
344 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
2 publications
293 citations
Centre Inria d'Université Côte d'Azur
Valbonne, France
2 h-index
2 publications
86 citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
2 h-index
2 publications
86 citations

Université Côte d'Azur
Nice, France
2 h-index
2 publications
86 citations
Lockheed Martin (United States)
Bethesda, United States
1 h-index
1 publications
14 citations
Kyushu University
Fukuoka, Japan
1 h-index
2 publications
22 citations

Southwest Research Institute
San Antonio, United States
1 h-index
1 publications
14 citations
1–8 of 20
1 publications · 15 citations
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1 publications · 43 citations
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1 publications · 12 citations
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1 publications · 14 citations
1
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1 publications · 39 citations
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