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An Active Learning Approach for Jointly Estimating Worker Performance
  and Annotation Reliability with Crowdsourced Data

An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data

16 January 2014
Liyue Zhao
Yu Zhang
G. Sukthankar
ArXiv (abs)PDFHTML

Papers citing "An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data"

2 / 2 papers shown
A Survey on Cost Types, Interaction Schemes, and Annotator Performance
  Models in Selection Algorithms for Active Learning in Classification
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in ClassificationIEEE Access (IEEE Access), 2021
M. Herde
Denis Huseljic
Bernhard Sick
A. Calma
242
32
0
23 Sep 2021
The future of human-AI collaboration: a taxonomy of design knowledge for
  hybrid intelligence systems
The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systemsHawaii International Conference on System Sciences (HICSS), 2019
Dominik Dellermann
A. Calma
Nikolaus Lipusch
Thorsten Weber
Sascha Weigel
P. Ebel
HAI
315
249
0
07 May 2021
1
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