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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:

Uncertainty-aware credit card fraud detection using deep learning
Maryam Habibpour, Hassan Gharoun, Mohammadreza Mehdipour, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106248-106248
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Uncertainty quantification of vibro-acoustic coupling problems for robotic manta ray models based on deep learning
Yilin Qu, Zhongbin Zhou, Leilei Chen, et al.
Ocean Engineering (2024) Vol. 299, pp. 117388-117388
Closed Access | Times Cited: 17
Deep-neural-network-based framework for the accelerating uncertainty quantification of a structural–acoustic fully coupled system in a shallow sea
Leilei Chen, Qing‐Xiang Pei, Z. Fei, et al.
Engineering Analysis with Boundary Elements (2025) Vol. 171, pp. 106112-106112
Closed Access | Times Cited: 2
Toward Efficient Credit Card Fraud Detection: Leveraging Quantum Neural Networks and Modified Feature Selection Techniques
N. Deepa, R. Jayaraj, M Suguna, et al.
Journal of Machine and Computing (2025), pp. 321-330
Closed Access
Development of Hybrid Intrusion Detection System Leveraging Ensemble Stacked Feature Selectors and Learning Classifiers to Mitigate the DoS Attacks
P. Mamatha, S. Balaji, S. Sai Anuraghav
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
A Sophisticated Iterative Weighted Feature Selection (IWFS) Based Spiking Imperialist Competitive Recurrent Neural Network (SICRNN) Classification Model for Credit Card Fraud Detection
S. Sobana, V. Diana Earshia, R. Suganthi, et al.
Iranian Journal of Science and Technology Transactions of Electrical Engineering (2025)
Closed Access
A Comparative analysis of Advanced Machine Learning Techniques for Enhancing Brain Tumor Detection
G. Nagaraju
Deleted Journal (2024) Vol. 20, Iss. 2s, pp. 901-909
Open Access | Times Cited: 3
Real-Time Online Banking Fraud Detection Model by Unsupervised Learning Fusion
H. A. Abbassi, Saida El Mendili, Youssef Gahi
HighTech and Innovation Journal (2024) Vol. 5, Iss. 1, pp. 185-199
Open Access | Times Cited: 3
Feature-wise attention based boosting ensemble method for fraud detection
Ruihao Cao, Junli Wang, Mingze Mao, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106975-106975
Closed Access | Times Cited: 6
Utilizing Blockchain and Deep Learning for Decentralized Discovery of Deceptive Practices in Healthcare Insurance
Nazeer Shaik, Nihar Ranjan Kar, Blessy Thankachan, et al.
(2023)
Closed Access | Times Cited: 5
The Role of Uncertainty Quantification for Trustworthy AI
Jessica Deuschel, Andreas Foltyn, Karsten Roscher, et al.
(2024), pp. 95-115
Closed Access | Times Cited: 1
Enhancing Credit Card Fraud Detection with Light Gradient-Boosting Machine: An Advanced Machine Learning Approach
S Sruthi, Siddharth Emadaboina, C. Jyotsna
(2024), pp. 1-6
Closed Access | Times Cited: 1
Enhanced autoencoder-based fraud detection: a novel approach with noise factor encoding and SMOTE
Mert Yılmaz Çakir, Yahya Şirin
Knowledge and Information Systems (2023) Vol. 66, Iss. 1, pp. 635-652
Closed Access | Times Cited: 3
Credit Card Fraud Detection with Subspace Learning-based One-Class Classification
Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, et al.
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2023), pp. 407-412
Open Access | Times Cited: 3
Improving MC-Dropout Uncertainty Estimates with Calibration Error-based Optimization.
Afshar Shamsi Jokandan, Hamzeh Asgharnezhad, Moloud Abdar, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 6
Machine Learning-Driven Detection and Prevention of Cryptocurrency Fraud
Anshika Sharma, Himanshi Babbar
(2023), pp. 1-5
Closed Access | Times Cited: 2
Enhancing Fraud Detection Capacities: The Role of Auditor Training, Professional Skepticism, and Integrity in Government Internal Control Mechanisms in Indonesia
Nurleni, Darmawati Darmawati, Mediaty MEDIATY
Revista de Gestão Social e Ambiental (2024) Vol. 18, Iss. 8, pp. e06002-e06002
Closed Access
Fuzzy Granular Computing for Evaluating Average Uncertainty in Machine Learning Models
Naimeh Sadeghi, Nima Gerami Seresht, Witold Pedrycz, et al.
(2024)
Closed Access
Enhancing Customer Experience through AI-Powered Personalization: A Data Science Perspective in E-Commerce
Hardeo Kumar Thakur, Jagendra Singh, A. Saxena, et al.
(2024), pp. 501-506
Closed Access
A Combinatorial Predictive Method for Fraud Identification to Uphold Security and Data Integrity
A. Anitha, Anjana Nair, Balakrishnan Kamaraj
Advances in business information systems and analytics book series (2024), pp. 272-305
Closed Access
Novel Methodology of Adaptive Machine Learning and Deep Learning System for Detecting the Fraudulent Activities in Financial Sector
Venkata Lakshmi Narayana G, Suvasini Panigrahi
(2024), pp. 1-6
Closed Access
Fraud Detection using Enhanced Secure Machine Learning Algorithm for Wireless Communication
N. Deepa, Ahmad Alkhayyat, Jayapal Lande, et al.
(2024), pp. 1-4
Closed Access
A distribution-preserving method for resampling combined with LightGBM-LSTM for sequence-wise fraud detection in credit card transactions
Behnam Yousefimehr, Mehdi Ghatee
Expert Systems with Applications (2024), pp. 125661-125661
Closed Access
A hybrid ensemble model to detect Bitcoin fraudulent transactions
Lifang Zhang, Xuan Ye, Zhenkun Liu, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 141, pp. 109810-109810
Closed Access
Uncertainty Quantification in Data Fusion Classifier for Ship-Wake Detection
Maice Costa, Daniel Sobien, Ria Garg, et al.
Remote Sensing (2024) Vol. 16, Iss. 24, pp. 4669-4669
Open Access
Neuroevolutionary Transfer Learning for Time Series Forecasting
Aymeric Vellinger, J. F. Torres, Federico Divina, et al.
Lecture notes in networks and systems (2023), pp. 219-228
Closed Access | Times Cited: 1
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