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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:

Credit Card Fraud Detection: A Realistic Modeling and a Novel Learning Strategy
Andrea Dal Pozzolo, Giacomo Boracchi, Olivier Caelen, et al.
IEEE Transactions on Neural Networks and Learning Systems (2017) Vol. 29, Iss. 8, pp. 3784-3797
Open Access | Times Cited: 447

Showing 1-25 of 447 citing articles:

Deep Learning for Anomaly Detection
Guansong Pang, Chunhua Shen, Longbing Cao, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 2, pp. 1-38
Open Access | Times Cited: 1535
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff, Jacob Kauffmann, Robert A. Vandermeulen, et al.
Proceedings of the IEEE (2021) Vol. 109, Iss. 5, pp. 756-795
Open Access | Times Cited: 690
Sequence classification for credit-card fraud detection
Johannes Jurgovsky, Michael Granitzer, Konstantin Ziegler, et al.
Expert Systems with Applications (2018) Vol. 100, pp. 234-245
Closed Access | Times Cited: 332
Combining unsupervised and supervised learning in credit card fraud detection
Fabrizio Carcillo, Yann‐Aël Le Borgne, Olivier Caelen, et al.
Information Sciences (2019) Vol. 557, pp. 317-331
Open Access | Times Cited: 317
An Intelligent Approach to Credit Card Fraud Detection Using an Optimized Light Gradient Boosting Machine
Altyeb Taha, Sharaf J. Malebary
IEEE Access (2020) Vol. 8, pp. 25579-25587
Open Access | Times Cited: 297
How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark
Nick Ryman‐Tubb, Paul Krause, Wolfgang Garn
Engineering Applications of Artificial Intelligence (2018) Vol. 76, pp. 130-157
Closed Access | Times Cited: 179
Real-time Credit Card Fraud Detection Using Machine Learning
Anuruddha Thennakoon, Chee Bhagyani, Sasitha Premadasa, et al.
2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (2019), pp. 488-493
Closed Access | Times Cited: 166
A Neural Network Ensemble With Feature Engineering for Improved Credit Card Fraud Detection
Ebenezer Esenogho, Ibomoiye Domor Mienye, Theo G. Swart, et al.
IEEE Access (2022) Vol. 10, pp. 16400-16407
Open Access | Times Cited: 150
Ensemble of deep sequential models for credit card fraud detection
Javad Forough, Saeedeh Momtazi
Applied Soft Computing (2020) Vol. 99, pp. 106883-106883
Closed Access | Times Cited: 140
Credit card fraud detection in the era of disruptive technologies: A systematic review
Asma Cherif, Arwa Badhib, Heyfa Ammar, et al.
Journal of King Saud University - Computer and Information Sciences (2022) Vol. 35, Iss. 1, pp. 145-174
Open Access | Times Cited: 85
Meta-learning approaches for learning-to-learn in deep learning: A survey
Yingjie Tian, Xiaoxi Zhao, Wei Huang
Neurocomputing (2022) Vol. 494, pp. 203-223
Closed Access | Times Cited: 84
A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions
Jonathan Kwaku Afriyie, Kassim Tawiah, Wilhemina Adoma Pels, et al.
Decision Analytics Journal (2023) Vol. 6, pp. 100163-100163
Open Access | Times Cited: 81
A stacking ensemble of deep learning models for IoT intrusion detection
Riccardo Lazzarini, Huaglory Tianfield, Vassilis Charissis
Knowledge-Based Systems (2023) Vol. 279, pp. 110941-110941
Open Access | Times Cited: 76
MSFlow: Multiscale Flow-Based Framework for Unsupervised Anomaly Detection
Yixuan Zhou, Xing Xu, Jingkuan Song, et al.
IEEE Transactions on Neural Networks and Learning Systems (2024) Vol. 36, Iss. 2, pp. 2437-2450
Open Access | Times Cited: 25
Champion-challenger analysis for credit card fraud detection: Hybrid ensemble and deep learning
Eunji Kim, Jehyuk Lee, Hunsik Shin, et al.
Expert Systems with Applications (2019) Vol. 128, pp. 214-224
Closed Access | Times Cited: 125
Supervised Machine Learning Algorithms for Credit Card Fraud Detection: A Comparison
Samidha Khatri, Aishwarya Arora, Arun Prakash Agrawal
2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (2020), pp. 680-683
Closed Access | Times Cited: 122
Credit Card Fraud Detection using Machine Learning and Data Science
S. P. Maniraj, Aditya Saini, Shadab Ahmed, et al.
International Journal of Engineering Research and (2019) Vol. 08, Iss. 09
Open Access | Times Cited: 119
Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs
Yvan Lucas, Pierre-Édouard Portier, Léa Laporte, et al.
Future Generation Computer Systems (2019) Vol. 102, pp. 393-402
Open Access | Times Cited: 118
LoRAS: an oversampling approach for imbalanced datasets
Saptarshi Bej, Narek Davtyan, Markus Wolfien, et al.
Machine Learning (2020) Vol. 110, Iss. 2, pp. 279-301
Open Access | Times Cited: 112
Credit Card Fraud Detection Using Random Forest Algorithm
M. Suresh Kumar, V. Soundarya, S. Kavitha, et al.
(2019), pp. 149-153
Closed Access | Times Cited: 103
Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection
Yingjie Zhou, Xucheng Song, Yanru Zhang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 6, pp. 2454-2465
Open Access | Times Cited: 99
Deep Representation Learning With Full Center Loss for Credit Card Fraud Detection
Zhenchuan Li, Guanjun Liu, Changjun Jiang
IEEE Transactions on Computational Social Systems (2020) Vol. 7, Iss. 2, pp. 569-579
Closed Access | Times Cited: 97
SCARFF : A scalable framework for streaming credit card fraud detection with spark
Fabrizio Carcillo, Andrea Dal Pozzolo, Yann‐Aël Le Borgne, et al.
Information Fusion (2017) Vol. 41, pp. 182-194
Open Access | Times Cited: 94
Auto loan fraud detection using dominance-based rough set approach versus machine learning methods
Jerzy Błaszczyński, Adiel Teixeira de Almeida Filho, Anna Matuszyk, et al.
Expert Systems with Applications (2020) Vol. 163, pp. 113740-113740
Closed Access | Times Cited: 94
Enhanced credit card fraud detection based on attention mechanism and LSTM deep model
Ibtissam Benchaji, Samira Douzi, Bouabid El Ouahidi, et al.
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 88
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