Resampling-based noise correction for crowdsourcing-Reference-Cited by-同舟云学术

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Resampling-based noise correction for crowdsourcing

Published:2020-08-17 Issue:6 Volume:33 Page:985-999
ISSN:0952-813X
Container-title:Journal of Experimental & Theoretical Artificial Intelligence
language:en
Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Xu Wenqiang¹,Jiang Liangxiao¹²^ORCID,Li Chaoqun³

Affiliation:

1. School of Computer Science, China University of Geosciences, Wuhan, China

2. Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China

3. School of Mathematics and Physics, China University of Geosciences, Wuhan, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1806519

Reference53 articles.

1. Crowdsourcing for search evaluation

2. Towards crowdsourcing translation tasks in library cataloguing, a pilot study

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Label noise correction for crowdsourcing using dynamic resampling;Engineering Applications of Artificial Intelligence;2024-07

2. Certainty weighted voting-based noise correction for crowdsourcing;Pattern Recognition;2024-06

3. Three-teaching: A three-way decision framework to handle noisy labels;Applied Soft Computing;2024-03

4. Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training;IEEE Access;2024

5. Improving label quality in crowdsourcing using deep co-teaching-based noise correction;International Journal of Machine Learning and Cybernetics;2023-05-10

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