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Liquid Crystals Volume 50, 2023 - Issue 7-10: In memoriam Maria Teresa Cidade, 28th International Liquid Crystal Conference (ILCC 2022); Guest editors: Maria Helena Godinho, Susete Nogueira Fernandes and Pedro Lúcio Almeida
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Mathematical Modelling, Symmetry and Topology

Classification of liquid crystal textures using convolutional neural networks

Ingo DierkingDepartment of Physics and Astronomy, The University of Manchester, Manchester, UKCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-8107-1342
ORCID Icon,
Jason DominguezDepartment of Physics and Astronomy, The University of Manchester, Manchester, UK
,
James HarbonDepartment of Physics and Astronomy, The University of Manchester, Manchester, UK
&
Joshua HeatonDepartment of Physics and Astronomy, The University of Manchester, Manchester, UK
Pages 1526-1540 | Received 12 Oct 2022, Published online: 02 Dec 2022

Citations (8)

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Read on this site (3)

Natalia Osiecka-Drewniak, Anna Drzewicz & Ewa Juszyńska-Gałązka. (2024) Machine learning studies for liquid crystal texture recognition. Liquid Crystals 51:2, pages 255-264.
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Natalia Osiecka-Drewniak, Marcin Piwowarczyk, Anna Drzewicz & Ewa Juszyńska-Gałązka. (2024) Liquid crystal textures, neural networks and art. Liquid Crystals 51:1, pages 128-135.
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Ingo Dierking, Jason Dominguez, James Harbon & Joshua Heaton. (2023) Testing different supervised machine learning architectures for the classification of liquid crystals. Liquid Crystals 50:7-10, pages 1461-1477.
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Articles from other publishers (5)

Natalia Osiecka-Drewniak, Aleksandra Deptuch, Magdalena Urbańska & Ewa Juszyńska-Gałązka. (2024) A Siamese neural network framework for glass transition recognition. Soft Matter 20:10, pages 2400-2406.
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Haijie Ren, Weiqiang Wang, Wentao Tang & Rui Zhang. (2024) Machine eye for defects: Machine learning-based solution to identify and characterize topological defects in textured images of nematic materials. Physical Review Research 6:1.
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Rebecca Betts & Ingo Dierking. (2024) Possibilities and limitations of convolutional neural network machine learning architectures in the characterisation of achiral orthogonal smectic liquid crystals. Soft Matter.
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Rebecca Betts & Ingo Dierking. (2023) Machine learning classification of polar sub-phases in liquid crystal MHPOBC. Soft Matter 19:39, pages 7502-7512.
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Jaka Zaplotnik, Jaka Pišljar, Miha Škarabot & Miha Ravnik. (2023) Neural networks determination of material elastic constants and structures in nematic complex fluids. Scientific Reports 13:1.
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