Scholar4AI Updated 2026-11-03 18:03 UTC+09:00

Papers on “noise robustness”

Research on “noise robustness” in the 480 tracked journals: papers per year and category, the journals, institutions and countries publishing it, the keywords studied with it and its most-cited papers. It is not among the most frequent keywords of the last 30 days, so this page has no list of its latest papers. Also as Markdown.

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← Top research keywords · Keyword trends

Key findings#

  • From 2017 to 2026 (so far), the keyword “noise robustness” appeared in 889 papers in the tracked journals, most of them in AI (845), operations research (23) and statistics (10).
  • 165 of them were published in 2025, against 33 in 2017.
  • Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (24), Northwestern Polytechnical University (23) and Sichuan University (20).
  • The journals publishing most of them were Expert Systems with Applications (96), Knowledge-Based Systems (67) and Pattern Recognition (63).
  • The most-cited of them is “Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017), with 533 citations.

Papers per year#

2017: 33 papers2018: 43 papers2019: 54 papers2020: 46 papers2021: 94 papers2022: 100 papers2023: 105 papers2024: 123 papers2025: 165 papers2026 (so far): 126 papers
20172026 (so far)
Papers per publication year and category
Category2017201820192020202120222023202420252026 (so far)
AI324251458894100120156117
Operations Research0001632155
Statistics1110012112
Information Systems0010010011
Economics0010010110
Higher Education and Research0000001001
Finance0000000010
All categories3343544694100105123165126

Where the papers come from#

Countries with the most papers, since 2023
#CountryPapers
1China399
2United States32
3India25
4Hong Kong24
5Australia20
6United Kingdom20
7Italy12
8Japan12
9France10
10Singapore10
Keywords with the most papers, since 2023
#KeywordPapers
1contrastive learning22
2feature selection22
3attention mechanism17
4convergence analysis16
5fault diagnosis15
6graph neural networks14
7image classification14
8multi-view clustering14
9self-supervised learning14

Most-cited papers#

Most-cited papers since 2017
#CitationsPer monthTitleJournalPublishedAuthors
15334.9Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust GatesIEEE Transactions on Pattern Analysis and Machine Intelligence2017-11-08Jun Liu, Amir Shahroudy, Dong Xu et al.
24834.6Significantly Fast and Robust Fuzzy C-Means Clustering Algorithm Based on Morphological Reconstruction and Membership FilteringIEEE Transactions on Fuzzy Systems2018-01-22Tao Lei, Xiaohong Jia, Yanning Zhang et al.
34326.2Graph Neural Networks with Convolutional ARMA FiltersIEEE Transactions on Pattern Analysis and Machine Intelligence2021-01-01Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi et al.
43865.7Speaker recognition based on deep learning: An overviewNeural Networks2021-03-18Zhongxin Bai, Xiao-Lei Zhang
52703.2Partition level multiview subspace clusteringNeural Networks2019-11-06Zhao Kang, Xinjia Zhao, Chong Peng et al.
Cite this page

Scholar4AI. (2026). Papers on “noise robustness”. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/keywords/noise-robustness

@misc{scholar4ai-keywords-noise-robustness,
  author = {{Scholar4AI}},
  title = {Papers on “noise robustness”},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/keywords/noise-robustness}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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