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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 of deep meta-learning
Mike Huisman, Jan N. van Rijn, Aske Plaat
Artificial Intelligence Review (2021) Vol. 54, Iss. 6, pp. 4483-4541
Open Access | Times Cited: 306

Showing 1-25 of 306 citing articles:

Explainable artificial intelligence: a comprehensive review
Dang Lien Minh, Hanxiang Wang, Yanfen Li, et al.
Artificial Intelligence Review (2021) Vol. 55, Iss. 5, pp. 3503-3568
Closed Access | Times Cited: 452
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 349
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects
Yong Feng, Jinglong Chen, Jingsong Xie, et al.
Knowledge-Based Systems (2021) Vol. 235, pp. 107646-107646
Closed Access | Times Cited: 166
Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis
Chuanjiang Li, Shaobo Li, Huan Wang, et al.
Knowledge-Based Systems (2023) Vol. 264, pp. 110345-110345
Open Access | Times Cited: 113
Meta-learning approaches for learning-to-learn in deep learning: A survey
Yingjie Tian, Xiaoxi Zhao, Wei Huang
Neurocomputing (2022) Vol. 494, pp. 203-223
Closed Access | Times Cited: 87
Few-Shot Learning With Class-Covariance Metric for Hyperspectral Image Classification
Bobo Xi, Jiaojiao Li, Yunsong Li, et al.
IEEE Transactions on Image Processing (2022) Vol. 31, pp. 5079-5092
Closed Access | Times Cited: 81
Face2Exp: Combating Data Biases for Facial Expression Recognition
Dan Zeng, Zhiyuan Lin, Yan Xiao, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2022), pp. 20259-20268
Closed Access | Times Cited: 75
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge
Liron Simon Keren, Alex Liberzon, Teddy Lazebnik
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 70
Revolutionizing drug formulation development: The increasing impact of machine learning
Zeqing Bao, Jack Bufton, Riley J. Hickman, et al.
Advanced Drug Delivery Reviews (2023) Vol. 202, pp. 115108-115108
Closed Access | Times Cited: 53
Meta Learning With Graph Attention Networks for Low-Data Drug Discovery
Qiujie Lv, Guanxing Chen, Ziduo Yang, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 8, pp. 11218-11230
Closed Access | Times Cited: 50
Advances and Challenges in Meta-Learning: A Technical Review
Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Joaquin Vanschoren, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 7, pp. 4763-4779
Open Access | Times Cited: 46
Meta-learning approaches for few-shot learning: A survey of recent advances
Hassan Gharoun, Fereshteh Momenifar, Fang Chen, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 12, pp. 1-41
Open Access | Times Cited: 22
Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning
Ziyi Zhou, Liang Zhang, Yuanxi Yu, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 22
Machine learning for industrial sensing and control: A survey and practical perspective
Nathan P. Lawrence, Seshu Kumar Damarla, Jong Woo Kim, et al.
Control Engineering Practice (2024) Vol. 145, pp. 105841-105841
Open Access | Times Cited: 20
Automated machine learning: past, present and future
Mitra Baratchi, Can Wang, Steffen Limmer, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 18
Distributed Machine Learning for Wireless Communication Networks: Techniques, Architectures, and Applications
Shuyan Hu, Xiaojing Chen, Wei Ni, et al.
IEEE Communications Surveys & Tutorials (2021) Vol. 23, Iss. 3, pp. 1458-1493
Open Access | Times Cited: 94
Subspace Network with Shared Representation learning for intelligent fault diagnosis of machine under speed transient conditions with few samples
Shen Liu, Jinglong Chen, Shuilong He, et al.
ISA Transactions (2021) Vol. 128, pp. 531-544
Closed Access | Times Cited: 83
Deep Siamese Semantic Segmentation Network for PCB Welding Defect Detection
Zhigang Ling, Aoran Zhang, Dexin Ma, et al.
IEEE Transactions on Instrumentation and Measurement (2022) Vol. 71, pp. 1-11
Closed Access | Times Cited: 63
Meta-features for meta-learning
Adriano Rívolli, Luís P. F. Garcia, Carlos Soares, et al.
Knowledge-Based Systems (2022) Vol. 240, pp. 108101-108101
Open Access | Times Cited: 60
Deep learning in periodontology and oral implantology: A scoping review
Hossein Mohammad‐Rahimi, Saeed Reza Motamedian, Zeynab Pirayesh, et al.
Journal of Periodontal Research (2022) Vol. 57, Iss. 5, pp. 942-951
Closed Access | Times Cited: 56
Multimodality in meta-learning: A comprehensive survey
Yao Ma, Shilin Zhao, Weixiao Wang, et al.
Knowledge-Based Systems (2022) Vol. 250, pp. 108976-108976
Open Access | Times Cited: 46
A deep spatio-temporal meta-learning model for urban traffic revitalization index prediction in the COVID-19 pandemic
Yue Wang, Zhiqiang Lv, Zhaoyu Sheng, et al.
Advanced Engineering Informatics (2022) Vol. 53, pp. 101678-101678
Closed Access | Times Cited: 44
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey
Amjad Yousef Majid, Serge Saaybi, Vincent François-Lavet, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 9, pp. 11939-11957
Open Access | Times Cited: 34
Deep image captioning: A review of methods, trends and future challenges
Liming Xu, Quan Tang, Jiancheng Lv, et al.
Neurocomputing (2023) Vol. 546, pp. 126287-126287
Closed Access | Times Cited: 31
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