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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:

DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem
Angélica Guzmán-Ponce, J. Salvador Sánchez, Rosa María Valdovinos Rosas, et al.
Expert Systems with Applications (2020) Vol. 168, pp. 114301-114301
Closed Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

AWGAN: An adaptive weighting GAN approach for oversampling imbalanced datasets
Shaopeng Guan, Xiaoyan Zhao, Yuewei Xue, et al.
Information Sciences (2024) Vol. 663, pp. 120311-120311
Closed Access | Times Cited: 20
On Supervised Class-Imbalanced Learning: An Updated Perspective and Some Key Challenges
Swagatam Das, Sankha Subhra Mullick, Ivan Zelinka
IEEE Transactions on Artificial Intelligence (2022) Vol. 3, Iss. 6, pp. 973-993
Closed Access | Times Cited: 40
A novel two-phase clustering-based under-sampling method for imbalanced classification problems
Aida Farshidvard, F. Hooshmand, S.A. MirHassani
Expert Systems with Applications (2022) Vol. 213, pp. 119003-119003
Closed Access | Times Cited: 38
A multiple combined method for rebalancing medical data with class imbalances
Yunchun Wang, Ching‐Hsue Cheng
Computers in Biology and Medicine (2021) Vol. 134, pp. 104527-104527
Closed Access | Times Cited: 48
A unified framework incorporating predictive generative denoising autoencoder and deep Coral network for rolling bearing fault diagnosis with unbalanced data
Xingqiu Li, Hongkai Jiang, Shaowei Liu, et al.
Measurement (2021) Vol. 178, pp. 109345-109345
Closed Access | Times Cited: 46
PF-SMOTE: A novel parameter-free SMOTE for imbalanced datasets
Qiong Chen, Zhong-Liang Zhang, Wenpo Huang, et al.
Neurocomputing (2022) Vol. 498, pp. 75-88
Closed Access | Times Cited: 36
A focal-aware cost-sensitive boosted tree for imbalanced credit scoring
Wanan Liu, Hong Fan, Min Xia, et al.
Expert Systems with Applications (2022) Vol. 208, pp. 118158-118158
Closed Access | Times Cited: 34
A cluster-based SMOTE both-sampling (CSBBoost) ensemble algorithm for classifying imbalanced data
Amirreza Salehi, Majid Khedmati
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
LDAS: Local density-based adaptive sampling for imbalanced data classification
Yuanting Yan, Yifei Jiang, Zhong Zheng, et al.
Expert Systems with Applications (2021) Vol. 191, pp. 116213-116213
Closed Access | Times Cited: 36
A combination of clustering-based under-sampling with ensemble methods for solving imbalanced class problem in intelligent systems
Mohammad Saleh Ebrahimi Shahabadi, Hamed Tabrizchi, Marjan Kuchaki Rafsanjani, et al.
Technological Forecasting and Social Change (2021) Vol. 169, pp. 120796-120796
Closed Access | Times Cited: 32
An Ensemble Learning Approach with Gradient Resampling for Class-Imbalance Problems
Hongke Zhao, Chuang Zhao, Xi Zhang, et al.
INFORMS journal on computing (2023) Vol. 35, Iss. 4, pp. 747-763
Closed Access | Times Cited: 15
NanBDOS: Adaptive and parameter-free borderline oversampling via natural neighbor search for class-imbalance learning
Qiangkui Leng, Jiamei Guo, Erjie Jiao, et al.
Knowledge-Based Systems (2023) Vol. 274, pp. 110665-110665
Closed Access | Times Cited: 14
An adaptive imbalance modified online broad learning system-based fault diagnosis for imbalanced chemical process data stream
Jinkun Men, C.M. Zhao
Expert Systems with Applications (2023) Vol. 234, pp. 121159-121159
Closed Access | Times Cited: 14
A majority affiliation based under-sampling method for class imbalance problem
Ying Xie, X. Huang, Feng Qin, et al.
Information Sciences (2024) Vol. 662, pp. 120263-120263
Closed Access | Times Cited: 4
LD-SMOTE: A Novel Local Density Estimation-Based Oversampling Method for Imbalanced Datasets
Jing Lyu, Jie Yang, Zhixun Su, et al.
Symmetry (2025) Vol. 17, Iss. 2, pp. 160-160
Open Access
DatRel: a noise-tolerant data relocation approach for effective synthetic data generation in imbalanced classifiers
Fatih Sağlam
Machine Learning (2025) Vol. 114, Iss. 5
Open Access
An adaptive multi-class imbalanced classification framework based on ensemble methods and deep network
Xuezheng Jiang, Junyi Wang, Qinggang Meng, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 15, pp. 11141-11159
Closed Access | Times Cited: 11
Entropy and improved k‐nearest neighbor search based under‐sampling (ENU) method to handle class overlap in imbalanced datasets
Anil Kumar, Dinesh Singh, Rama Shankar Yadav
Concurrency and Computation Practice and Experience (2023) Vol. 36, Iss. 2
Closed Access | Times Cited: 11
SOM-US: A Novel Under-Sampling Technique for Handling Class Imbalance Problem
Ajay Kumar
Journal of Communications Software and Systems (2024) Vol. 20, Iss. 1, pp. 69-75
Open Access | Times Cited: 3
A multi-level classification based ensemble and feature extractor for credit risk assessment
Yuanyuan Wang, Zhuang Wu, Jing Gao, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1915-e1915
Open Access | Times Cited: 3
Toward hierarchical classification of imbalanced data using random resampling algorithms
Rodolfo M. Pereira, Yandre M. G. Costa, Carlos N. Silla
Information Sciences (2021) Vol. 578, pp. 344-363
Closed Access | Times Cited: 22
Variational Autoencoder Based Imbalanced COVID-19 Detection Using Chest X-Ray Images
Sankhadeep Chatterjee, Soumyajit Maity, Mayukh Bhattacharjee, et al.
New Generation Computing (2022) Vol. 41, Iss. 1, pp. 25-60
Open Access | Times Cited: 12
GAN-Based Multi-Task Learning Approach for Prognostics and Health Management of IIoT
Sourajit Behera, Rajiv Misra, Alberto Sillitti
IEEE Transactions on Automation Science and Engineering (2023) Vol. 21, Iss. 3, pp. 2742-2762
Closed Access | Times Cited: 7
Alleviating Class Imbalance Issue in Software Fault Prediction Using DBSCAN-Based Induced Graph Under-Sampling Method
Kirti Bhandari, Kuldeep Kumar, Amrit Lal Sangal
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 9, pp. 12589-12627
Closed Access | Times Cited: 2
OBMI: oversampling borderline minority instances by a two-stage Tomek link-finding procedure for class imbalance problem
Qiangkui Leng, Jiamei Guo, Jiaqing Tao, et al.
Complex & Intelligent Systems (2024) Vol. 10, Iss. 4, pp. 4775-4792
Open Access | Times Cited: 2
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