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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:

Learning imbalanced datasets based on SMOTE and Gaussian distribution
Tingting Pan, Junhong Zhao, Wei Wu, et al.
Information Sciences (2019) Vol. 512, pp. 1214-1233
Closed Access | Times Cited: 152

Showing 1-25 of 152 citing articles:

DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
Suriya Murugan, Chandran Venkatesan, M. G. Sumithra, et al.
IEEE Access (2021) Vol. 9, pp. 90319-90329
Open Access | Times Cited: 211
A novel oversampling technique for class-imbalanced learning based on SMOTE and natural neighbors
Junnan Li, Qingsheng Zhu, Quanwang Wu, et al.
Information Sciences (2021) Vol. 565, pp. 438-455
Closed Access | Times Cited: 145
SMOTE-RkNN: A hybrid re-sampling method based on SMOTE and reverse k-nearest neighbors
Aimin Zhang, Hualong Yu, Zhangjun Huan, et al.
Information Sciences (2022) Vol. 595, pp. 70-88
Closed Access | Times Cited: 75
A survey on imbalanced learning: latest research, applications and future directions
Wuxing Chen, Kaixiang Yang, Zhiwen Yu, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 6
Open Access | Times Cited: 47
Electricity theft detection in low-voltage stations based on similarity measure and DT-KSVM
Xiangyu Kong, Xin Zhao, Chao Liu, et al.
International Journal of Electrical Power & Energy Systems (2020) Vol. 125, pp. 106544-106544
Closed Access | Times Cited: 85
SMOTEFUNA: Synthetic Minority Over-Sampling Technique Based on Furthest Neighbour Algorithm
Ahmad S. Tarawneh, Ahmad B. Hassanat, Khalid Almohammadi, et al.
IEEE Access (2020) Vol. 8, pp. 59069-59082
Open Access | Times Cited: 69
SMOTE-NaN-DE: Addressing the noisy and borderline examples problem in imbalanced classification by natural neighbors and differential evolution
Junnan Li, Qingsheng Zhu, Quanwang Wu, et al.
Knowledge-Based Systems (2021) Vol. 223, pp. 107056-107056
Closed Access | Times Cited: 69
A New Oversampling Method Based on the Classification Contribution Degree
Zhenhao Jiang, Tingting Pan, Chao Zhang, et al.
Symmetry (2021) Vol. 13, Iss. 2, pp. 194-194
Open Access | Times Cited: 68
Augmented data driven self-attention deep learning method for imbalanced fault diagnosis of the HVAC chiller
Cunxiao Shen, Hanyuan Zhang, Songping Meng, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105540-105540
Closed Access | Times Cited: 50
A Synthetic Minority Oversampling Technique Based on Gaussian Mixture Model Filtering for Imbalanced Data Classification
Zhaozhao Xu, Derong Shen, Yue Kou, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 3, pp. 3740-3753
Closed Access | Times Cited: 41
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
Application of machine learning technology for occupational accident severity prediction in the case of construction collapse accidents
Xixi Luo, Xinchun Li, Zaili Yang, et al.
Safety Science (2023) Vol. 163, pp. 106138-106138
Closed Access | Times Cited: 26
CHSMOTE: Convex hull-based synthetic minority oversampling technique for alleviating the class imbalance problem
Xiaohan Yuan, Shuyu Chen, Han Zhou, et al.
Information Sciences (2022) Vol. 623, pp. 324-341
Closed Access | Times Cited: 29
Self-adaptive oversampling method based on the complexity of minority data in imbalanced datasets classification
Xinmin Tao, Xinyue Guo, Yujia Zheng, et al.
Knowledge-Based Systems (2023) Vol. 277, pp. 110795-110795
Closed Access | Times Cited: 18
An improved generative adversarial network to oversample imbalanced datasets
Tingting Pan, Witold Pedrycz, Jie Yang, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 132, pp. 107934-107934
Closed Access | Times Cited: 7
Data Augmentation for Electricity Theft Detection Using Conditional Variational Auto-Encoder
Xuejiao Gong, Tang Bo, Ruijin Zhu, et al.
Energies (2020) Vol. 13, Iss. 17, pp. 4291-4291
Open Access | Times Cited: 39
Class imbalance learning using fuzzy ART and intuitionistic fuzzy twin support vector machines
Salim Rezvani, Xizhao Wang
Information Sciences (2021) Vol. 578, pp. 659-682
Closed Access | Times Cited: 39
Random and Synthetic Over-Sampling Approach to Resolve Data Imbalance in Classification
Mardhiya Hayaty, Siti Muthmainah, Syed Muhammad Ghufran
International Journal of Artificial Intelligence Research (2021) Vol. 4, Iss. 2, pp. 86-86
Open Access | Times Cited: 32
Subspace-based minority oversampling for imbalance classification
Tianjun Li, Yingxu Wang, Licheng Liu, et al.
Information Sciences (2022) Vol. 621, pp. 371-388
Closed Access | Times Cited: 25
An empirical study on the joint impact of feature selection and data resampling on imbalance classification
Chongsheng Zhang, Paolo Soda, Jingjun Bi, et al.
Applied Intelligence (2022)
Closed Access | Times Cited: 24
Dementia Classification Using Deep Reinforcement Learning for Early Diagnosis
Arshad Hashmi, Omar Barukab
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1464-1464
Open Access | Times Cited: 14
An efficient framework based on local multi-representatives and noise-robust synthetic example generation for self-labeled semi-supervised classification
Junnan Li, Shun Fu, Wei Fu, et al.
Neural Networks (2025) Vol. 185, pp. 107142-107142
Closed Access
Enhancing Prediction Accuracy for High-dimensional Small-sample-size Microarray Data Cancer by Combining Chebyshev Interpolation with New Dual-net GAN
Liang-Sian Lin, Yao-San Lin, Der‐Chiang Li, et al.
Applied Soft Computing (2025), pp. 112826-112826
Closed Access
Hybridization of DEBOHID with ENN algorithm for highly imbalanced datasets
Sedat Korkmaz
Engineering Science and Technology an International Journal (2025) Vol. 63, pp. 101976-101976
Closed Access
Stacked CNN-based multichannel attention networks for Alzheimer disease detection
Najmul Hassan, Abu Saleh Musa Miah, Kota Suzuki, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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