Preface.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. N.PAG, doi. 10.3934/ammc.2023013
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Works matching IS 29947669 AND DT 2023 AND VI 1 AND IP 2
Results: 8
1
2
Model-based deep learning approaches to the Helsinki Tomography Challenge 2022.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023007
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- Article
3
Limited-angle tomography reconstruction via deep end-to-end learning on synthetic data.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023006
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- Publication type:
- Article
4
Helsinki tomography challenge 2022: Description of the competition and dataset.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023010
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- Publication type:
- Article
5
HD-DCDM: Hybrid-domain network for limited-angle computed tomography with deconvolution and conditional diffusion model.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. N.PAG, doi. 10.3934/ammc.2023008
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- Publication type:
- Article
6
A directional regularization method for the limited-angle Helsinki Tomography Challenge using the Core Imaging Library (CIL).
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023011
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- Publication type:
- Article
7
A deep learning approach using boundary shape information for limited-angle tomography reconstruction.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023012
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- Publication type:
- Article
8
Deep image prior with sparsity constraint for limited-angle computed tomography reconstruction.
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- Applied Mathematics for Modern Challenges, 2023, v. 1, n. 2, p. 1, doi. 10.3934/ammc.2023009
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- Publication type:
- Article