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A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction
Research article (Composites Part A Applied Science and Manufacturing, 2024) · cited 20× · AI/ML
A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction is a scholarly article[1].
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A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-self-supervised-learning-framework-based-on-physics-informed-and-convolutional-neural-networks-to-identify-local-aniso
MLA“A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-self-supervised-learning-framework-based-on-physics-informed-and-convolutional-neural-networks-to-identify-local-aniso.
BibTeX@misc{4ortxyz_a-self-supervised-learning-framework-based-on-physics-informed-and-convolutional-neural-networks-to-identify-local-aniso_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction}}, year = {2026}, url = {https://4ort.xyz/entity/a-self-supervised-learning-framework-based-on-physics-informed-and-convolutional-neural-networks-to-identify-local-aniso}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction — https://4ort.xyz/entity/a-self-supervised-learning-framework-based-on-physics-informed-and-convolutional-neural-networks-to-identify-local-aniso (retrieved 2026-05-24)
