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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Contrastive label correction for noisy label learning
Bin Huang, Yaohai Lin, Chaoyang Xu
Information Sciences (2022) Vol. 611, pp. 173-184
Closed Access | Times Cited: 15

Showing 15 citing articles:

Cross-to-merge training with class balance strategy for learning with noisy labels
Qian Zhang, Yi Zhu, Ming Yang, et al.
Expert Systems with Applications (2024) Vol. 249, pp. 123846-123846
Open Access | Times Cited: 17
Bayesian DivideMix++ for Enhanced Learning with Noisy Labels
Bhalaji Nagarajan, Ricardo Marques, Eduardo Aguilar, et al.
Neural Networks (2024) Vol. 172, pp. 106122-106122
Closed Access | Times Cited: 8
Learning with noisy labels via clean aware sharpness aware minimization
Bin Huang, Ying Xie, Chaoyang Xu
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
TCC-net: A two-stage training method with contradictory loss and co-teaching based on meta-learning for learning with noisy labels
Qiangqiang Xia, Feifei Lee, Qiu Chen
Information Sciences (2023) Vol. 639, pp. 119008-119008
Closed Access | Times Cited: 15
ECLB: Efficient contrastive learning on bi-level for noisy labels
Juwei Guan, Jiaxiang Liu, Shuying Huang, et al.
Knowledge-Based Systems (2024) Vol. 300, pp. 112128-112128
Closed Access | Times Cited: 4
A label noise filtering method for regression based on adaptive threshold and noise score
Chuang Li, Zhizhong Mao
Expert Systems with Applications (2023) Vol. 228, pp. 120422-120422
Closed Access | Times Cited: 9
Combining layered label correction and mixup supervised contrastive learning to learn noisy labels
Bin Huang, Ping Zhang, Chaoyang Xu
Information Sciences (2023) Vol. 642, pp. 119242-119242
Closed Access | Times Cited: 7
Psscl: A Progressive Sample Selection Framework with Contrastive Loss Designed for Noisy Labels
Qian Zhang, Yi Zhu, Filipe R. Cordeiro, et al.
(2024)
Closed Access | Times Cited: 1
A Two-Stage Noisy Label Learning Framework with Uniform Consistency Selection and Robust Training
Qian Zhang, Chen Qiu
(2024)
Closed Access | Times Cited: 1
Tackling Biased Complementary Label Learning with Large Margin
Yiwei You, Jinglong Huang, Q.K. Tong, et al.
Information Sciences (2024) Vol. 687, pp. 121400-121400
Closed Access | Times Cited: 1
Label correction using contrastive prototypical classifier for noisy label learning
Chaoyang Xu, Renjie Lin, Jinyu Cai, et al.
Information Sciences (2023) Vol. 649, pp. 119647-119647
Closed Access | Times Cited: 4
Supervised contrastive learning with corrected labels for noisy label learning
Jihong Ouyang, Chenyang Lu, Bing Wang, et al.
Applied Intelligence (2023) Vol. 53, Iss. 23, pp. 29378-29392
Closed Access | Times Cited: 3
Learning with noisy labels via clean-aware sharpness-aware minimization
Bin Huang, Ping Zhang, Ying Xie, et al.
Research Square (Research Square) (2024)
Closed Access
Randomly shuffled convolution for self-supervised representation learning
Young-Jin Oh, Min-Kyu Jeon, Dohwan Ko, et al.
Information Sciences (2022) Vol. 623, pp. 206-219
Open Access | Times Cited: 2
Multi Combination Pattern Labeling by using Deep Learning for Chameleon Rotary Machine Environment
Jieun Kang, SuBi Kim, Yong-Ik Yoon
Research Square (Research Square) (2022)
Open Access
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