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Pan Zhu, Shijie Yan, Xinglin Zhou
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Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review
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A speckling technique for DIC on ultra-soft, highly hydrated materials
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Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals
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Directional DIC method with automatic feature selection
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When deep learning meets digital image correlation
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Unsupervised CNN-based DIC method for 2D displacement measurement
10.1016/j.optlaseng.2023.107981 · 2024
Deep DIC: deep learning-based digital image correlation for end-to-end displacement and strain measurement
10.1016/j.jmatprotec.2021.117474 · 2022
StrainNet-LD: large displacement digital image correlation based on deep learning and displacement-field decomposition
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Efficient and robust deformation measurement based on unsupervised learning
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Stereo-DICNet: an efficient and unified speckle matching network for stereo digital image correlation measurement
10.1016/j.optlaseng.2024.108267 · 2024
Deep 3D-DIC using a coarse-to-fine network for robust and accurate 3D shape and displacement measurements
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Transformer based deep learning for digital image correlation
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Sub-pixel displacement measurement with swin transformer: a three-level classification approach
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Transformer-enhanced end-to-end models for accurate displacement and strain fields in digital image correlation
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10.1007/s11340-015-0009-1 · doi-reference
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10.1016/j.softx.2019.100391 · doi-reference
Hyperspectral image classification based on ConvGRU and spectral–spatial joint attention
10.1016/j.asoc.2025.112949 · doi-reference
Transformer-enhanced end-to-end models for accurate displacement and strain fields in digital image correlation
10.1364/oe.553602 · doi-reference
Sub-pixel displacement measurement with swin transformer: a three-level classification approach
10.3390/app15052868 · doi-reference
A gated recurrent units (GRU)-based model for early detection of soybean sudden death syndrome through time-series satellite imagery
10.3390/rs12213621 · doi-reference
DIC-net: upgrade the performance of traditional DIC with hermite dataset and convolution neural network
10.1016/j.optlaseng.2022.107278 · doi-reference
SigMa: semantic similarity-guided semi-dense feature matching
10.1109/tip.2026.3654367 · doi-reference
Transformer based deep learning for digital image correlation
10.1016/j.optlaseng.2024.108568 · doi-reference
Deep 3D-DIC using a coarse-to-fine network for robust and accurate 3D shape and displacement measurements
10.1364/oe.549759 · doi-reference
Stereo-DICNet: an efficient and unified speckle matching network for stereo digital image correlation measurement
10.1016/j.optlaseng.2024.108267 · doi-reference
Efficient and robust deformation measurement based on unsupervised learning
10.1016/j.measurement.2024.115908 · doi-reference
StrainNet-LD: large displacement digital image correlation based on deep learning and displacement-field decomposition
10.1016/j.optlaseng.2024.108502 · doi-reference
Deep DIC: deep learning-based digital image correlation for end-to-end displacement and strain measurement
10.1016/j.jmatprotec.2021.117474 · doi-reference
Unsupervised CNN-based DIC method for 2D displacement measurement
10.1016/j.optlaseng.2023.107981 · doi-reference
When deep learning meets digital image correlation
10.1016/j.optlaseng.2020.106308 · doi-reference
Directional DIC method with automatic feature selection
10.1016/j.ymssp.2024.112080 · doi-reference
A review of speckle pattern fabrication and assessment for digital image correlation
10.1007/s11340-017-0283-1 · doi-reference
Speckle pattern quality assessment for digital image correlation
10.1016/j.optlaseng.2013.03.014 · doi-reference
Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals
10.1088/1361-6501/aac55b · doi-reference
A speckling technique for DIC on ultra-soft, highly hydrated materials
10.1007/s11340-023-00938-x · doi-reference
Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review
10.1088/0957-0233/20/6/062001 · doi-reference