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:

A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection
Emilija Strelcenia, Simant Prakoonwit
Machine Learning and Knowledge Extraction (2023) Vol. 5, Iss. 1, pp. 304-329
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Utilizing GANs for fraud detection: model training with synthetic transaction data
Mengran Zhu, Yulu Gong, Yafei Xiang, et al.
(2024) Vol. 5, pp. 310-310
Open Access | Times Cited: 19

A Hybrid Framework for Predicting Crash Severity in Construction Work Zones Using Knowledge Distillation and Conditional GANs
Ali Hassandokht Mashhadi, Abbas Rashidi, Juan C. Medina, et al.
Journal of Computing in Civil Engineering (2025) Vol. 39, Iss. 2
Closed Access

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index
Qiangwei Li, Xin Gao, Heping Lu, et al.
Neural Networks (2025) Vol. 185, pp. 107126-107126
Closed Access

Procedural game level generation with GANs: potential, weaknesses, and unresolved challenges in the literature
Daniele Fernandes E. Silva, Rafael Torchelsen, Marílton Sanchotene de Aguiar
Multimedia Tools and Applications (2025)
Closed Access

Deep learning in pediatric neuroimaging
Jian Wang, Jiaji Wang, Shuihua Wang‎, et al.
Displays (2023) Vol. 80, pp. 102583-102583
Open Access | Times Cited: 10

A Hybrid Deep Learning Approach with Generative Adversarial Network for Credit Card Fraud Detection
Ibomoiye Domor Mienye, Theo G. Swart
Technologies (2024) Vol. 12, Iss. 10, pp. 186-186
Open Access | Times Cited: 3

Comparing Resampling Techniques in Stroke Prediction with Machine and Deep Learning
M. Roshni Thanka, Kommu Sri Ram, Shalem Preetham Gandu, et al.
(2023)
Closed Access | Times Cited: 9

Comparative Effectiveness of Data Augmentation Using Traditional Approaches versus StyleGANs in Automated Sewer Defect Detection
Qianqian Zhou, Zuxiang Situ, Shuai Teng, et al.
Journal of Water Resources Planning and Management (2023) Vol. 149, Iss. 9
Closed Access | Times Cited: 8

CasTGAN: Cascaded Generative Adversarial Network for Realistic Tabular Data Synthesis
Abdallah Alshantti, Damiano Varagnolo, Adil Rasheed, et al.
IEEE Access (2024) Vol. 12, pp. 13213-13232
Open Access | Times Cited: 2

Improving deep learning in arrhythmia Detection: The application of modular quality and quantity controllers in data augmentation
Mohammad Usef Khosravi Khaliran, Iman Zabbah, Mehrbod Faraji, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 105940-105940
Closed Access | Times Cited: 2

Lane Segmentation Data Augmentation for Heavy Rain Sensor Blockage Using Realistically Translated Raindrop Images and CARLA Simulator
Jinu Pahk, Seongjeong Park, Jungseok Shim, et al.
IEEE Robotics and Automation Letters (2024) Vol. 9, Iss. 6, pp. 5488-5495
Closed Access | Times Cited: 2

An Improved YOLOv5 for Accurate Detection and Localization of Tomato and Pepper Leaf Diseases
Balkis Tej, Soulef Bouaafia, Mohamed Ali Hajjaji, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 1

Diffusion-based Wasserstein generative adversarial network for blood cell image augmentation
Emmanuel Edward Ngasa, Mi‐Ae Jang, Servas Adolph Tarimo, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108221-108221
Closed Access | Times Cited: 1

Real-Time Detection of Customer-Induced Damage in Printed Circuit Boards Using Mobile Devices and YOLO Detectors
J. Santiago, Victor A. E. Farias, Lucas Sena, et al.
Learning and Nonlinear Models (2024) Vol. 22, Iss. 1, pp. 17-31
Open Access | Times Cited: 1

Generative Adversarial Networks-Based Novel Approach for Fraud Detection for the European Cardholders 2013 Dataset
Fahdah Almarshad, Ghada Abdalaziz Gashgari, Abdullah I. A. Alzahrani
IEEE Access (2023) Vol. 11, pp. 107348-107368
Open Access | Times Cited: 4

Towards data generation to alleviate privacy concerns for cybersecurity applications
Dhiraj Ganji, Chandranil Chakraborttii
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC) (2023), pp. 1447-1452
Closed Access | Times Cited: 2

A Comparative Analysis of Fraud Detection from Diverse Datasets to Algorithmic Performance
Can İşcan, Mehmet Akif Nardemir, Fatma Patlar Akbulut
2021 6th International Conference on Computer Science and Engineering (UBMK) (2023), pp. 543-547
Closed Access | Times Cited: 2

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: 2

Exploring Supervised Machine Learning Techniques for Detecting Credit Card Fraud: An Investigative Review
Amit Patel, Manish I. Patel, Pankaj Patel
ITM Web of Conferences (2024) Vol. 65, pp. 03006-03006
Open Access

Melanoma classification using generative adversarial network and proximal policy optimization
Xiangui Ju, Chi‐Ho Lin, Suan Lee, et al.
Photochemistry and Photobiology (2024)
Closed Access

Improving Insurance Fraud Detection With Generated Data
Kiet Ha, Lucas Stowe, Chandranil Chakraborttii
2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC) (2024), pp. 2008-2013
Closed Access

A New Image Oversampling Method Based on Influence Functions and Weights
Jun Ye, Shoulei Lu, Jiawei Chen
Applied Sciences (2024) Vol. 14, Iss. 22, pp. 10553-10553
Open Access

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