Shape Reconstruction Optimization
Shape Reconstruction Optimization is a shape optimization method that specifically seeks to determine an optimal geometric configuration by minimizing discrepancies between observed data and numerically simulated boundary or field responses, distinguished from other shape optimization approaches by its primary focus on inferring or reconstructing a target shape from indirect, often incomplete or noisy, measurements through iterative refinement.
39
Publications
1.6K
Citations
121
Authors
58
Institutions
Publications per year
2017–2026
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Centre National de la Recherche Scientifique
Paris, France
3 h-index
7 publications
177 citations
Université de Bourgogne
Dijon, France
2 h-index
6 publications
166 citations

Cornell University
Ithaca, United States
2 h-index
4 publications
112 citations
Tsinghua University
Beijing, China
2 h-index
5 publications
199 citations
Gunma University
Maebashi, Japan
2 h-index
2 publications
84 citations

Kiryu University
Midori, Japan
2 h-index
2 publications
84 citations
University of Bonn
Bonn, Germany
1 h-index
3 publications
396 citations
Wuhan University of Technology
Wuhan, China
1 h-index
5 publications
85 citations
1–8 of 58
TPAMI · 2 publications · 160 citations
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1 publications · 17 citations
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1 publications · 29 citations
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1 publications · 10 citations
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1 publications · 86 citations
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