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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:

LLE Score: A New Filter-Based Unsupervised Feature Selection Method Based on Nonlinear Manifold Embedding and Its Application to Image Recognition
Chao Yao, Ya‐Feng Liu, Bo Jiang, et al.
IEEE Transactions on Image Processing (2017) Vol. 26, Iss. 11, pp. 5257-5269
Closed Access | Times Cited: 101

Showing 1-25 of 101 citing articles:

A Review of Feature Selection and Its Methods
B. Venkatesh, J. Anuradha
Cybernetics and Information Technologies (2019) Vol. 19, Iss. 1, pp. 3-26
Open Access | Times Cited: 498
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Mohammad Tubishat, Norisma Idris, Liyana Shuib, et al.
Expert Systems with Applications (2019) Vol. 145, pp. 113122-113122
Closed Access | Times Cited: 327
End-to-end video background subtraction with 3d convolutional neural networks
Dimitrios Sakkos, Heng Liu, Jungong Han, et al.
Multimedia Tools and Applications (2017) Vol. 77, Iss. 17, pp. 23023-23041
Closed Access | Times Cited: 119
Unsupervised Feature Extraction in Hyperspectral Images Based on Wasserstein Generative Adversarial Network
Mingyang Zhang, Maoguo Gong, Yishun Mao, et al.
IEEE Transactions on Geoscience and Remote Sensing (2018) Vol. 57, Iss. 5, pp. 2669-2688
Closed Access | Times Cited: 114
Top-k Feature Selection Framework Using Robust 0–1 Integer Programming
Xiaoqin Zhang, Mingyu Fan, Di Wang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 7, pp. 3005-3019
Closed Access | Times Cited: 106
Feature Selection and Its Use in Big Data: Challenges, Methods, and Trends
Rong Miao, Dunwei Gong, Xiao‐Zhi Gao
IEEE Access (2019) Vol. 7, pp. 19709-19725
Open Access | Times Cited: 92
A hybrid forecasting framework based on support vector regression with a modified genetic algorithm and a random forest for traffic flow prediction
Lizong Zhang, Nawaf Alharbe, Guangchun Luo, et al.
Tsinghua Science & Technology (2018) Vol. 23, Iss. 4, pp. 479-492
Open Access | Times Cited: 84
Unsupervised feature selection via adaptive autoencoder with redundancy control
Xiaoling Gong, Ling Yu, Jian Wang, et al.
Neural Networks (2022) Vol. 150, pp. 87-101
Closed Access | Times Cited: 64
Multi-label feature selection via latent representation learning and dynamic graph constraints
Yao Zhang, Wei Huo, Jun Tang
Pattern Recognition (2024) Vol. 151, pp. 110411-110411
Closed Access | Times Cited: 14
Unsupervised Discriminative Feature Selection via Contrastive Graph Learning
Qian Zhou, Qianqian Wang, Quanxue Gao, et al.
IEEE Transactions on Image Processing (2024) Vol. 33, pp. 972-986
Closed Access | Times Cited: 10
Sparse multi-label feature selection via pseudo-label learning and dynamic graph constraints
Yao Zhang, Jun Tang, Ziqiang Cao, et al.
Information Fusion (2025), pp. 102975-102975
Closed Access | Times Cited: 1
Hierarchical Feature Selection for Random Projection
Qi Wang, Jia Wan, Feiping Nie, et al.
IEEE Transactions on Neural Networks and Learning Systems (2018) Vol. 30, Iss. 5, pp. 1581-1586
Closed Access | Times Cited: 78
Graph regularized locally linear embedding for unsupervised feature selection
Jianyu Miao, Tiejun Yang, Lijun Sun, et al.
Pattern Recognition (2021) Vol. 122, pp. 108299-108299
Closed Access | Times Cited: 52
Non-negative multi-label feature selection with dynamic graph constraints
Zhang Yao, Yingcang Ma
Knowledge-Based Systems (2021) Vol. 238, pp. 107924-107924
Closed Access | Times Cited: 49
Multi-view unsupervised feature selection with tensor low-rank minimization
Haoliang Yuan, Junyu Li, Yong Liang, et al.
Neurocomputing (2022) Vol. 487, pp. 75-85
Closed Access | Times Cited: 32
Unsupervised feature selection through combining graph learning and ℓ2,0-norm constraint
Peican Zhu, Xin Hou, Keke Tang, et al.
Information Sciences (2022) Vol. 622, pp. 68-82
Closed Access | Times Cited: 32
A new univariate feature selection algorithm based on the best–worst multi-attribute decision-making method
Dharyll Prince Abellana, Demelo M. Lao
Decision Analytics Journal (2023) Vol. 7, pp. 100240-100240
Open Access | Times Cited: 16
Adaptive dynamic elite opposition-based Ali Baba and the forty thieves algorithm for high-dimensional feature selection
Malik Braik, Mohammed A. Awadallah, Hussein Al-Zoubi, et al.
Cluster Computing (2024) Vol. 27, Iss. 8, pp. 10487-10523
Closed Access | Times Cited: 6
Accelerating information entropy-based feature selection using rough set theory with classified nested equivalence classes
Jie Zhao, Jiaming Liang, Zhenning Dong, et al.
Pattern Recognition (2020) Vol. 107, pp. 107517-107517
Closed Access | Times Cited: 47
A Comparison of Three Classification Algorithms for Handwritten Digit Recognition
Maiwan Bahjat Abdulrazzaq, Jwan Najeeb Saeed
(2019)
Closed Access | Times Cited: 45
High-order conditional mutual information maximization for dealing with high-order dependencies in feature selection
Francisco Souza, Cristiano Premebida, Rui Araújo
Pattern Recognition (2022) Vol. 131, pp. 108895-108895
Open Access | Times Cited: 24
Multiobjective optimization algorithm with dynamic operator selection for feature selection in high-dimensional classification
Wenhong Wei, Manlin Xuan, Lingjie Li, et al.
Applied Soft Computing (2023) Vol. 143, pp. 110360-110360
Closed Access | Times Cited: 15
Spatial distribution and source identification of potentially toxic elements in Yellow River Delta soils, China: An interpretable machine-learning approach
Mengge Zhou, Yonghua Li
The Science of The Total Environment (2023) Vol. 912, pp. 169092-169092
Closed Access | Times Cited: 15
Bi-level ensemble method for unsupervised feature selection
Peng Zhou, Xia Wang, Liang Du
Information Fusion (2023) Vol. 100, pp. 101910-101910
Closed Access | Times Cited: 13
Effective theory building and manifold learning
D. Freeborn
Synthese (2025) Vol. 205, Iss. 1
Open Access
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