Redundancy Elimination
Redundancy Elimination is a methodological process in data management that systematically identifies and removes duplicate or superfluous data entries within a core collection to enhance data quality and efficiency while preserving informational integrity.
317
Publications
18.3K
Citations
902
Authors
361
Institutions
Publications per year
2017–2026
60
317
Visual Tracking with Fully Convolutional Networks
Lijun Wang, Wanli Ouyang, Xiaogang Wang et al. · 2015 · 1K citations
Stephan Schulz · 2002 · 418 citations
1–5 of 317
902
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h-index
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1–5 of 902
361

Centre National de la Recherche Scientifique
Paris, France
10 h-index
20 publications
1.6K citations
Carnegie Mellon University
Pittsburgh, United States
7 h-index
9 publications
654 citations

Rice University
Houston, United States
7 h-index
14 publications
805 citations
University of Wisconsin–Madison
Madison, United States
7 h-index
19 publications
2.3K citations
IBM (United States)
Armonk, United States
7 h-index
13 publications
1.5K citations

University of Minnesota
Minneapolis, United States
6 h-index
20 publications
676 citations
University of Pittsburgh
Pittsburgh, United States
6 h-index
11 publications
509 citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
9 publications
170 citations
1–8 of 361
15 publications · 465 citations
13
h-index
Repository · 5 publications · 381 citations
5
h-index
TODS · 4 publications · 251 citations
4
h-index
TPDS · 4 publications · 146 citations
4
h-index
3 publications · 129 citations
3
h-index
1–5