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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:

MCDAL: Maximum Classifier Discrepancy for Active Learning
Jae Won Cho, Dong-Jin Kim, YunJae Jung, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 34, Iss. 11, pp. 8753-8763
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

DASO: Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning
Young‐Taek Oh, Dong-Jin Kim, In So Kweon
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022)
Open Access | Times Cited: 60
Active Teacher for Semi-Supervised Object Detection
Peng Mi, Jianghang Lin, Yiyi Zhou, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 14462-14471
Open Access | Times Cited: 50
A Multimodal Auxiliary Classification System for Osteosarcoma Histopathological Images Based on Deep Active Learning
Fangfang Gou, Jun Liu, Jun Zhu, et al.
Healthcare (2022) Vol. 10, Iss. 11, pp. 2189-2189
Open Access | Times Cited: 28
PT4AL: Using Self-supervised Pretext Tasks for Active Learning
John Seon Keun Yi, Minseok Seo, Jongchan Park, et al.
Lecture notes in computer science (2022), pp. 596-612
Open Access | Times Cited: 23
Focus on informative graphs! Semi-supervised active learning for graph-level classification
Wei Ju, Zhengyang Mao, Ziyue Qiao, et al.
Pattern Recognition (2024) Vol. 153, pp. 110567-110567
Closed Access | Times Cited: 5
Boosting active learning via re-aligned feature space
Tianxiang Yin, Ningzhong Liu, Han Sun, et al.
Knowledge-Based Systems (2025) Vol. 311, pp. 113085-113085
Closed Access
Discriminative fault diagnosis transfer learning network under joint mechanism
Yuxuan Yang, Jing Jiang, Jian Zhang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Batch active learning for time-series classification with multi-mode exploration
Sangho Lee, Chihyeon Choi, Hyungrok Do, et al.
Information Sciences (2025), pp. 122109-122109
Closed Access
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Inkyu Shin, Dong-Jin Kim, Jae Won Cho, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Open Access | Times Cited: 31
A novel anomaly detection approach based on ensemble semi-supervised active learning (ADESSA)
Zequn Niu, Xu‐Guang Guo, Jingfeng Xue, et al.
Computers & Security (2023) Vol. 129, pp. 103190-103190
Closed Access | Times Cited: 11
Federated Active Learning (F-AL): An Efficient Annotation Strategy for Federated Learning
Jin-Hyun Ahn, Yeeun Ma, Seoyun Park, et al.
IEEE Access (2024) Vol. 12, pp. 39261-39269
Open Access | Times Cited: 4
An efficient framework based on local multi-representatives and noise-robust synthetic example generation for self-labeled semi-supervised classification
Junnan Li, Shun Fu, Wei Fu, et al.
Neural Networks (2025) Vol. 185, pp. 107142-107142
Closed Access
Uncertainty-weighted prototype active learning in domain adaptive semantic segmentation
Zihao Dong, Sijie Niu, Xizhan Gao, et al.
Expert Systems with Applications (2024) Vol. 245, pp. 123094-123094
Closed Access | Times Cited: 3
Unsupervised Selective Labeling for More Effective Semi-supervised Learning
Xudong Wang, Long Lian, Stella X. Yu
Lecture notes in computer science (2022), pp. 427-445
Closed Access | Times Cited: 14
Active Learning for Handling Missing Data
Alaa Tharwat, Wolfram Schenck
IEEE Transactions on Neural Networks and Learning Systems (2024) Vol. 36, Iss. 2, pp. 3273-3287
Open Access | Times Cited: 2
Prototype Guided Pseudo Labeling and Perturbation-based Active Learning for domain adaptive semantic segmentation
Junkun Peng, Mingjie Sun, Eng Gee Lim, et al.
Pattern Recognition (2023) Vol. 148, pp. 110203-110203
Closed Access | Times Cited: 4
WMBAL: weighted minimum bounds for active learning
Shuai Lü, Jiaxi Zheng, Zhi Li, et al.
Applied Intelligence (2024) Vol. 54, Iss. 3, pp. 2551-2563
Closed Access | Times Cited: 1
BALQUE: Batch active learning by querying unstable examples with calibrated confidence
Yincheng Han, Dajiang Liu, Jiaxing Shang, et al.
Pattern Recognition (2024) Vol. 151, pp. 110385-110385
Closed Access | Times Cited: 1
Semi-supervised batch active learning based on mutual information
Xia Ji, Limin Wang, Fang Xu
Applied Intelligence (2024) Vol. 55, Iss. 2
Closed Access | Times Cited: 1
Local pseudo-attributes for long-tailed recognition
Dong-Jin Kim, Tsung-Wei Ke, Stella X. Yu
Pattern Recognition Letters (2023) Vol. 172, pp. 51-57
Closed Access | Times Cited: 3
Source-Free Active Domain Adaptation via Augmentation-Based Sample Query and Progressive Model Adaptation
Shuang Li, Rui Zhang, Kaixiong Gong, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 36, Iss. 2, pp. 2538-2550
Closed Access | Times Cited: 3
Federated Learning-Based Analysis of Human Sentiments and Physical Activities in Natural Disasters
Muhammad Amin, Woong-Kee Loh
Applied Sciences (2023) Vol. 13, Iss. 5, pp. 2925-2925
Open Access | Times Cited: 2
Modeling Semantic Correlation and Hierarchy for Real-World Wildlife Recognition
Dong-Jin Kim, Zhongqi Miao, Yunhui Guo, et al.
IEEE Signal Processing Letters (2023) Vol. 30, pp. 259-263
Closed Access | Times Cited: 2
Multi-Classifier Adversarial Optimization for Active Learning
Lin Geng, Ningzhong Liu, Jie Qin
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 6, pp. 7687-7695
Open Access | Times Cited: 2
Spectral Transfer Guided Active Domain Adaptation For Thermal Imagery
Berkcan Ustun, Ahmet Kağan Kaya, Ezgi Cakir Ayerden, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2023), pp. 449-458
Open Access | Times Cited: 2
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