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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:

The role of convolutional neural networks in scanning probe microscopy: a review
Ido Azuri, Irit Rosenhek‐Goldian, Neta Regev‐Rudzki, et al.
Beilstein Journal of Nanotechnology (2021) Vol. 12, pp. 878-901
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning
Maxim Ziatdinov, Yongtao Liu, Kyle P. Kelley, et al.
ACS Nano (2022) Vol. 16, Iss. 9, pp. 13492-13512
Open Access | Times Cited: 53
Deep learning modeling in microscopy imaging: A review of materials science applications
Marco Ragone, Reza Shahabazian-Yassar, Farzad Mashayek, et al.
Progress in Materials Science (2023) Vol. 138, pp. 101165-101165
Open Access | Times Cited: 21
Application of self-organizing maps to AFM-based viscoelastic characterization of breast cancer cell mechanics
Andreas Weber, María dM Vivanco, José L. Toca‐Herrera
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17
On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition
Igor Sokolov
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 15, pp. 11263-11270
Open Access | Times Cited: 6
Atomic force microscopy in the characterization and clinical evaluation of neurological disorders: current and emerging technologies
David T. She, Mui Hoon Nai, Chwee Teck Lim
Med-X (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 6
Autonomous scanning probe microscopy investigations over WS2 and Au{111}
John C. Thomas, Antonio Rossi, Darian Smalley, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 20
Data-driven analysis for the evaluation of cortical mechanics of non-adherent cells
Nicholas Hallfors, Charalampos Lamprou, Shaohong Luo, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Financial Transactional Fraud Detection using a Hybrid BiLSTM with Attention-Based Autoencoder
K Sudharson, S Varsha, S. Rajalakshmi, et al.
International Research Journal of Multidisciplinary Technovation (2025), pp. 135-147
Open Access
Electrostatic Discovery Atomic Force Microscopy
Niko Oinonen, Chen Xu, Benjamin Alldritt, et al.
ACS Nano (2021) Vol. 16, Iss. 1, pp. 89-97
Open Access | Times Cited: 21
Correction of AFM data artifacts using a convolutional neural network trained with synthetically generated data
Viktor Kocur, Veronika Hegrová, Marek Patočka, et al.
Ultramicroscopy (2022) Vol. 246, pp. 113666-113666
Closed Access | Times Cited: 13
Machine learning-aided atomic structure identification of interfacial ionic hydrates from AFM images
Binze Tang, Yizhi Song, Mian Qin, et al.
National Science Review (2022) Vol. 10, Iss. 7
Open Access | Times Cited: 12
How scanning probe microscopy can be supported by artificial intelligence and quantum computing?
Agnieszka Pręgowska, Agata Roszkiewicz, Magdalena Osial, et al.
Microscopy Research and Technique (2024)
Open Access | Times Cited: 2
Deep learning strategy for small dataset from atomic force microscopy mechano-imaging on macrophages phenotypes
Hao Wu, Lei Zhang, Banglei Zhao, et al.
Frontiers in Bioengineering and Biotechnology (2023) Vol. 11
Open Access | Times Cited: 6
Geometric Back-propagation in Morphological Neural Networks
Rick Groenendijk, Leo Dorst, Theo Gevers
IEEE Transactions on Pattern Analysis and Machine Intelligence (2023), pp. 1-8
Open Access | Times Cited: 5
Machine Learning Approaches for Stem Cells
M. Mazalan, Tien-Dung Do, Wan Safwani Wan Kamarul Zaman, et al.
Current Stem Cell Reports (2023) Vol. 9, Iss. 3, pp. 43-56
Closed Access | Times Cited: 5
Detecting atomic-scale surface defects in STM of TMDs with ensemble deep learning
Darian Smalley, Stephanie D. Lough, Luke Holtzman, et al.
MRS Advances (2024) Vol. 9, Iss. 11, pp. 890-896
Closed Access | Times Cited: 1
Machine Learning Allows for Distinguishing Precancerous and Cancerous Human Epithelial Cervical Cells Using High-Resolution AFM Imaging of Adhesion Maps
М. П. Петров, Igor Sokolov
Cells (2023) Vol. 12, Iss. 21, pp. 2536-2536
Open Access | Times Cited: 3
Some considerations in nanoindentation measurement and analysis by atomic force microscopy
Irit Rosenhek‐Goldian, Sidney Cohen
Journal of Vacuum Science & Technology A Vacuum Surfaces and Films (2023) Vol. 41, Iss. 6
Open Access | Times Cited: 3
Generalised deep-learning workflow for the prediction of hydration layers over surfaces
Yashasvi S. Ranawat, Ygor Morais Jaques, Adam S. Foster
Journal of Molecular Liquids (2022) Vol. 367, pp. 120571-120571
Open Access | Times Cited: 3
Nanobiomechanical data classified by Deep learning based on convolutional neural networks
Adrián Martínez-Rivas, Cécile Formosa‐Dague, Luis Emilio Magaña Espinal, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Leveraging Artificial Intelligence and Reverse Tip Sample Configuration for Automation of Data Processing in Quantitative Scanning Spreading Resistance Microscopy
Lennaert Wouters, Katrin Peters, Pieter Lagrain, et al.
physica status solidi (a) (2024)
Open Access
Geometric Back-Propagation in Morphological Neural Networks
Rick Groenendijk, L. Dorst, T. Gevers
(2022)
Open Access | Times Cited: 1
Deep Learning-Based Approach for Classifying the Severity of Metal Corrosion Using Sem Images
Saranga Veeramangal Hebbar, Basheera M. Mahmmod, Iznora Aini Zolkifly, et al.
Lecture notes on data engineering and communications technologies (2023), pp. 403-418
Closed Access
Deep Learning to Predict Structure-Property Relationships of Polymer Blends
Dalia G. Yablon, Ishita Chakraborty, Hillary Passino, et al.
ACS symposium series (2022), pp. 51-64
Closed Access
Geometric Back-Propagation in Morphological Neural Networks
Rick Groenendijk, L. Dorst, T. Gevers
(2022)
Open Access
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