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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:

Testing different supervised machine learning architectures for the classification of liquid crystals
Ingo Dierking, Jason Dominguez, James Harbon, et al.
Liquid Crystals (2023) Vol. 50, Iss. 7-10, pp. 1461-1477
Open Access | Times Cited: 9

Showing 9 citing articles:

Machine learning methods for liquid crystal research: phases, textures, defects and physical properties
Anastasiia Piven, Darina Darmoroz, Ekaterina V. Skorb, et al.
Soft Matter (2024) Vol. 20, Iss. 7, pp. 1380-1391
Closed Access | Times Cited: 9
Quantifying memory: detection of focal conic domain rearrangement across a phase transition
Sean Hare, Alexander de la Vega, Francesca Serra
Soft Matter (2025) Vol. 21, Iss. 10, pp. 1907-1914
Closed Access
Convolutional neural network analysis of optical texture patterns in liquid-crystal skyrmions
J. Terroa, Mykola Tasinkevych, C. S. Dias
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine learning classification of polar sub-phases in liquid crystal MHPOBC
Rebecca Betts, Ingo Dierking
Soft Matter (2023) Vol. 19, Iss. 39, pp. 7502-7512
Open Access | Times Cited: 9
Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials
Haijie Ren, Weiqiang Wang, Wentao Tang, et al.
Physical Review Research (2024) Vol. 6, Iss. 1
Open Access | Times Cited: 2
The use of artificial intelligence in liquid crystal applications: A review
Sarah Chattha, Philip K. Chan, Simant R. Upreti
The Canadian Journal of Chemical Engineering (2024)
Open Access | Times Cited: 2
A Siamese neural network framework for glass transition recognition
Natalia Osiecka, Aleksandra Deptuch, Magdalena Urbańska, et al.
Soft Matter (2024) Vol. 20, Iss. 10, pp. 2400-2406
Closed Access | Times Cited: 1
Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals
R. P. Betts, Ingo Dierking
Soft Matter (2024) Vol. 20, Iss. 21, pp. 4226-4236
Open Access | Times Cited: 1
Machine learning studies for liquid crystal texture recognition
Natalia Osiecka, Anna Drzewicz, Ewa Juszyńska‐Gałązka
Liquid Crystals (2023) Vol. 51, Iss. 2, pp. 255-264
Closed Access | Times Cited: 3
Prediction of the Structural Color of Liquid Crystals via Machine Learning
Andrew T. Nguyen, Heather M. Childs, William M. Salter, et al.
Liquids (2023) Vol. 3, Iss. 4, pp. 440-455
Open Access | Times Cited: 1
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