Quality Measure Optimization
Quality Measure Optimization is a methodological framework within grasp quality assessment that systematically enhances the evaluation of robotic grasp stability and effectiveness by refining the mathematical and computational criteria used to quantify grasp performance.
71
Publications
4.7K
Citations
213
Authors
106
Institutions
Publications per year
2017–2026
10
Parents
71
Ulrik Brandes, Daniel Delling, Marco Gaertler et al. · IEEE Transactions on Knowledge and Data Engineering · 2008 · 1.3K citations · Full text
Approximate join processing over data streams
Abhinandan Das, Johannes Gehrke, Mirek Riedewald · 2003 · 277 citations
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University of Illinois Urbana-Champaign, United States
2 publications · 107 citations
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1–5 of 213
106
Carnegie Mellon University
Pittsburgh, United States
3 h-index
8 publications
330 citations
Karlsruhe Institute of Technology
Karlsruhe, Germany
3 h-index
10 publications
5.3K citations

Cornell University
Ithaca, United States
2 h-index
6 publications
1K citations
Stony Brook University
Stony Brook, United States
2 h-index
2 publications
45 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
5 publications
469 citations
Georgia Institute of Technology
Atlanta, United States
2 h-index
3 publications
84 citations
University of Maryland, Baltimore County
Baltimore, United States
2 h-index
4 publications
69 citations
Technical University of Munich
Munich, Germany
2 h-index
3 publications
43 citations
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IJRR · 2 publications · 112 citations
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2 publications · 387 citations
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2 publications · 151 citations
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2 publications · 80 citations
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1 publications · 69 citations
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