Inter-annotator Agreement
Inter-Annotator Agreement is a measurement metric used in image annotation that quantifies the degree of consensus among multiple human annotators in assigning labels to visual data, distinguishing itself from other evaluation metrics by focusing specifically on the reliability and consistency of annotations rather than model performance.
490
Publications
27.4K
Citations
1.8K
Authors
623
Institutions
Publications per year
2017–2026
195
Variants
Iaa
Parents
490
Vikas C. Raykar, Shipeng Yu, Linda Zhao et al. · Journal of Machine Learning Research · 2010 · 1K citations
Automatic Evaluation of Topic Coherence
David Newman, Jey Han Lau, Karl Grieser et al. · 2010 · 730 citations
The Kappa Statistic: A Second Look
Barbara Di Eugenio, Michael Glass · Computational Linguistics · 2004 · 498 citations · Full text
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University of Pennsylvania
Philadelphia, United States
12 h-index
23 publications
3.4K citations
University of Cambridge
Cambridge, United Kingdom
11 h-index
32 publications
4.4K citations
University of Southern California
Los Angeles, United States
10 h-index
58 publications
2.8K citations
Columbia University
New York, United States
10 h-index
20 publications
793 citations

Johns Hopkins University
Baltimore, United States
9 h-index
15 publications
1.2K citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
26 publications
1.2K citations
University of Pittsburgh
Pittsburgh, United States
9 h-index
21 publications
988 citations

University of Edinburgh
Edinburgh, United Kingdom
9 h-index
22 publications
2.7K citations
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Repository · 20 publications · 540 citations
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10 publications · 2.2K citations
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9 publications · 556 citations
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Repository · 9 publications · 440 citations
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JAMIA · 8 publications · 490 citations
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