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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 systematic study of the class imbalance problem in convolutional neural networks
Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski
Neural Networks (2018) Vol. 106, pp. 249-259
Open Access | Times Cited: 2244

Showing 1-25 of 2244 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: 8963
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: 2096
Class-Balanced Loss Based on Effective Number of Samples
Yin Cui, Menglin Jia, Tsung-Yi Lin, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019)
Open Access | Times Cited: 1923
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
Pranav Rajpurkar, Jeremy Irvin, Kaylie Zhu, et al.
arXiv (Cornell University) (2017)
Closed Access | Times Cited: 941
COVIDiagnosis-Net: Deep Bayes-SqueezeNet based diagnosis of the coronavirus disease 2019 (COVID-19) from X-ray images
Ferhat Uçar, Deniz Korkmaz
Medical Hypotheses (2020) Vol. 140, pp. 109761-109761
Open Access | Times Cited: 747
BBN: Bilateral-Branch Network With Cumulative Learning for Long-Tailed Visual Recognition
Boyan Zhou, Quan Cui, Xiu-Shen Wei, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 9716-9725
Open Access | Times Cited: 696
Data imbalance in classification: Experimental evaluation
Fadi Thabtah, Suhel Hammoud, Firuz Kamalov, et al.
Information Sciences (2019) Vol. 513, pp. 429-441
Closed Access | Times Cited: 588
Augmentation for small object detection
Máté Kisantal, Zbigniew Wojna, Jakub Murawski, et al.
(2019)
Open Access | Times Cited: 557
Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI
Maciej A. Mazurowski, Mateusz Buda, Ashirbani Saha, et al.
Journal of Magnetic Resonance Imaging (2018) Vol. 49, Iss. 4, pp. 939-954
Open Access | Times Cited: 438
Deep learning algorithms for rotating machinery intelligent diagnosis: An open source benchmark study
Zhibin Zhao, Tianfu Li, Jingyao Wu, et al.
ISA Transactions (2020) Vol. 107, pp. 224-255
Open Access | Times Cited: 426
Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues
Abhishek Gupta, Alagan Anpalagan, Ling Guan, et al.
Array (2021) Vol. 10, pp. 100057-100057
Open Access | Times Cited: 402
Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia
Xi Ouyang, Jiayu Huo, Liming Xia, et al.
IEEE Transactions on Medical Imaging (2020) Vol. 39, Iss. 8, pp. 2595-2605
Open Access | Times Cited: 376
Deep Learning for the Radiographic Detection of Periodontal Bone Loss
Joachim Krois, Thomas Ekert, Leonie Meinhold, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 348
Maintaining Discrimination and Fairness in Class Incremental Learning
Bowen Zhao, Xi Xiao, Guojun Gan, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 13205-13214
Open Access | Times Cited: 346
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 338
Deep learning in bioinformatics: Introduction, application, and perspective in the big data era
Yu Li, Chao Huang, Lizhong Ding, et al.
Methods (2019) Vol. 166, pp. 4-21
Open Access | Times Cited: 333
Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting
Jun Shu, Qi Xie, Lixuan Yi, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 327
Identifying animal species in camera trap images using deep learning and citizen science
Marco Willi, Ross T. Pitman, Anabelle W. Cardoso, et al.
Methods in Ecology and Evolution (2018) Vol. 10, Iss. 1, pp. 80-91
Open Access | Times Cited: 319
Convolutional Neural Networks for the Automatic Identification of Plant Diseases
Justine Boulent, Samuel Foucher, Jérôme Théau, et al.
Frontiers in Plant Science (2019) Vol. 10
Open Access | Times Cited: 305
Deep Learning for the Radiographic Detection of Apical Lesions
Thomas Ekert, Joachim Krois, Leonie Meinhold, et al.
Journal of Endodontics (2019) Vol. 45, Iss. 7, pp. 917-922.e5
Closed Access | Times Cited: 283
Detecting mammals in UAV images: Best practices to address a substantially imbalanced dataset with deep learning
Benjamin Kellenberger, Diego Marcos, Devis Tuia
Remote Sensing of Environment (2018) Vol. 216, pp. 139-153
Open Access | Times Cited: 282
A deep translation (GAN) based change detection network for optical and SAR remote sensing images
Xinghua Li, Zhengshun Du, Yanyuan Huang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 179, pp. 14-34
Open Access | Times Cited: 275
Hidden stratification causes clinically meaningful failures in machine learning for medical imaging
Luke Oakden‐Rayner, Jared Dunnmon, Gustavo Carneiro, et al.
(2020), pp. 151-159
Open Access | Times Cited: 272
Long-tail learning via logit adjustment
Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 264
IL2M: Class Incremental Learning With Dual Memory
Eden Belouadah, Adrian Popescu
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 583-592
Open Access | Times Cited: 260
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