Data Labeling
Data Labeling is the process of assigning meaningful categorical or descriptive tags to raw data instances in order to transform them into annotated datasets suitable for supervised machine learning.
208
Publications
20.1K
Citations
756
Authors
284
Institutions
Publications per year
2017–2026
154
Parents
208
Combining labeled and unlabeled data with co-training
Avrim Blum, Tom M. Mitchell · 1998 · 5.6K citations · Full text
A brief introduction to weakly supervised learning
Zhi‐Hua Zhou · National Science Review · 2017 · 1.9K citations · Full text
SLEAP: A deep learning system for multi-animal pose tracking
Talmo Pereira, Nathaniel Tabris, Arie Matsliah et al. · Nature Methods · 2022 · 904 citations · Full text
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284
New York University
New York, United States
7 h-index
17 publications
6.6K citations
University of Washington
Seattle, United States
6 h-index
15 publications
500 citations
Stanford University
Stanford, United States
6 h-index
26 publications
6K citations
Microsoft (United States)
Redmond, United States
5 h-index
26 publications
1.6K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
15 publications
11.6K citations
Simon Fraser University
Burnaby, Canada
4 h-index
7 publications
231 citations

National Taiwan University
Taipei, Taiwan
4 h-index
14 publications
600 citations
University of Pennsylvania
Philadelphia, United States
4 h-index
4 publications
180 citations
1–8 of 284
Repository · 11 publications · 465 citations
11
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10 publications · 320 citations
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TKDE · 4 publications · 1K citations
4
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4 publications · 147 citations
4
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3 publications · 80 citations
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