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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:

A survey on addressing high-class imbalance in big data
Joffrey L. Leevy, Taghi M. Khoshgoftaar, Richard A. Bauder, et al.
Journal Of Big Data (2018) Vol. 5, Iss. 1
Open Access | Times Cited: 623

Showing 1-25 of 623 citing articles:

A survey on Image Data Augmentation for Deep Learning
Connor Shorten, Taghi M. Khoshgoftaar
Journal Of Big Data (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 9031
Survey on deep learning with class imbalance
Justin Johnson, Taghi M. Khoshgoftaar
Journal Of Big Data (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 2112
CatBoost for big data: an interdisciplinary review
John Hancock, Taghi M. Khoshgoftaar
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 828
Imbalance Problems in Object Detection: A Review
Kemal Öksüz, Barış Can Çam, Sinan Kalkan, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020) Vol. 43, Iss. 10, pp. 3388-3415
Open Access | Times Cited: 451
A survey and performance evaluation of deep learning methods for small object detection
Yang Liu, Peng Sun, Nickolas M. Wergeles, et al.
Expert Systems with Applications (2021) Vol. 172, pp. 114602-114602
Closed Access | Times Cited: 392
Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective
Iqbal H. Sarker
SN Computer Science (2021) Vol. 2, Iss. 5
Open Access | Times Cited: 314
Deep Learning applications for COVID-19
Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 303
Boosting methods for multi-class imbalanced data classification: an experimental review
Jafar Tanha, Yousef Abdi, Negin Samadi, et al.
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 289
Resampling imbalanced data for network intrusion detection datasets
Sikha Bagui, Kunqi Li
Journal Of Big Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 202
Human Digital Twin for Fitness Management
Barbara Rita Barricelli, Elena Casiraghi, Jessica Gliozzo, et al.
IEEE Access (2020) Vol. 8, pp. 26637-26664
Open Access | Times Cited: 188
Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks
K. Ruwani M. Fernando, Chris P. Tsokos
IEEE Transactions on Neural Networks and Learning Systems (2021) Vol. 33, Iss. 7, pp. 2940-2951
Closed Access | Times Cited: 184
A survey and analysis of intrusion detection models based on CSE-CIC-IDS2018 Big Data
Joffrey L. Leevy, Taghi M. Khoshgoftaar
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 170
A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization
Gehad Ismail Sayed, Mona Soliman, Aboul Ella Hassanien
Computers in Biology and Medicine (2021) Vol. 136, pp. 104712-104712
Closed Access | Times Cited: 159
Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing
Sheng Wang, Kaiyu Guan, Chenhui Zhang, et al.
Remote Sensing of Environment (2022) Vol. 271, pp. 112914-112914
Open Access | Times Cited: 133
A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation
Azal Ahmad Khan, Omkar Chaudhari, Rohitash Chandra
Expert Systems with Applications (2023) Vol. 244, pp. 122778-122778
Open Access | Times Cited: 117
CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems
Neha Gupta, Vinita Jindal, Punam Bedi
Computers & Security (2021) Vol. 112, pp. 102499-102499
Closed Access | Times Cited: 104
Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease Classification
Sabbir Ahmed, Md. Bakhtiar Hasan, Tasnim Ahmed, et al.
IEEE Access (2022) Vol. 10, pp. 68868-68884
Open Access | Times Cited: 103
A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis
Andrew Rawson, Mario Brito
Transport Reviews (2022) Vol. 43, Iss. 1, pp. 108-130
Open Access | Times Cited: 73
Attack Classification of Imbalanced Intrusion Data for IoT Network Using Ensemble-Learning-Based Deep Neural Network
Ankit Thakkar, Ritika Lohiya
IEEE Internet of Things Journal (2023) Vol. 10, Iss. 13, pp. 11888-11895
Closed Access | Times Cited: 70
Generalizable machine learning for stress monitoring from wearable devices: A systematic literature review
Gideon Vos, Kelly Trinh, Zoltán Sarnyai, et al.
International Journal of Medical Informatics (2023) Vol. 173, pp. 105026-105026
Open Access | Times Cited: 60
Cost-sensitive learning for imbalanced medical data: a review
Imane Araf, Ali Idri, Ikram Chairi
Artificial Intelligence Review (2024) Vol. 57, Iss. 4
Open Access | Times Cited: 23
Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data
Cynthia Yang, Egill A. Friðgeirsson, Jan A. Kors, et al.
Journal Of Big Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 16
Efficient hybrid oversampling and intelligent undersampling for imbalanced big data classification
Carla Vairetti, José Luis Assadi, Sebastián Maldonado
Expert Systems with Applications (2024) Vol. 246, pp. 123149-123149
Open Access | Times Cited: 16
Feature selection and its combination with data over-sampling for multi-class imbalanced datasets
Chih‐Fong Tsai, Kuan-Chen Chen, Wei‐Chao Lin
Applied Soft Computing (2024) Vol. 153, pp. 111267-111267
Closed Access | Times Cited: 15
Leveraging Generative Adversarial Networks for Data Augmentation to Improve Fault Detection in Wind Turbines with Imbalanced Data
Subhajit Chatterjee, Yung-Cheol Byun
Results in Engineering (2025), pp. 103991-103991
Open Access | Times Cited: 3
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