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sparse reconstruction

Dictionary learning based sinogram inpainting for CT sparse reconstruction

Dictionary learning based sinogram inpainting for CT sparse reconstruction

... Inpainting 350.71 4 Conclusion In this paper, a dictionary based sinogram inpainting method is proposed to compensate the artifact problem in CT sparse reconstruction. The patch-based dictionary is first ...

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Sparse reconstruction from Multiple-Angle Total Internal Reflection Fluorescence Microscopy

Sparse reconstruction from Multiple-Angle Total Internal Reflection Fluorescence Microscopy

... 3. SPARSE RECONSTRUCTION METHOD 3.1. Optimization Problem Formulation Finding a solution of the ill-posed inverse problem (P) (i.e deter- mine f in (P) from acquisition s) can be formulated as a minimiza- ...

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Sparse reconstruction of the dark matter mass map from weak gravitational lensing

Sparse reconstruction of the dark matter mass map from weak gravitational lensing

... on sparse regularisation which makes use of higher order lensing informa- tion in order to improve the resolution of the mass map and allow the detection of small substruc- ...The sparse ...

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Orthogonal greedy algorithms for non-negative sparse reconstruction

Orthogonal greedy algorithms for non-negative sparse reconstruction

... the grid for sparse reconstruction has step ∆ = 0.5. Each atom is a delayed version of the previous atom by a step ∆. to increase the rate of recycled wood in the production of new particleboards. In this ...

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Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

... [7] Y. Hu, L. Xie, L. Luo, J.-C. Nunes, and C. Toumoulin, “L0 con- strained sparse reconstruction for multi-slice helical CT reconstruc- tion”, Physics in Medicine and Biology, 56, vol. 4, pp. 1173–89, ...

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L0 constrained sparse reconstruction for multi-slice helical CT reconstruction.

L0 constrained sparse reconstruction for multi-slice helical CT reconstruction.

... highly sparse sampled ...iterative reconstruction method using L0-norm prior has been designed for multislice helical ...under sparse signals, a well known highly ill-posed ...for ...

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Sparse reconstruction techniques for near-field underwater acoustic imaging

Sparse reconstruction techniques for near-field underwater acoustic imaging

... Nikolaos Stefanakis, Jacques Marchal, Valentin Emiya, Nancy Bertin, Rémi Gribonval, Pierre Cervenka.. To cite this version:a[r] ...

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Hierarchical Bayesian sparse image reconstruction with application to MRFM

Hierarchical Bayesian sparse image reconstruction with application to MRFM

... reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian ...naturally sparse image applications as it seamlessly accounts for ...

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Accelerated parallel magnetic resonance imaging reconstruction using joint estimation with a sparse signal model

Accelerated parallel magnetic resonance imaging reconstruction using joint estimation with a sparse signal model

... the reconstruction of multiple channel images rather than a single combined ...the sparse reconstruction prob- lem and devise a method for Joint estimation from Undersam- pled LinEs in Parallel MRI ...

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Simple envelope-based reconstruction methods can infer light partitioning among individual plants in sparse and dense herbaceous canopies

Simple envelope-based reconstruction methods can infer light partitioning among individual plants in sparse and dense herbaceous canopies

... and leaf area properties (total plant area, leaf dispersion and leaf angles). Relative size between plants (and more particularly relative height) was shown to be crucial at HD, but had a minor role in sparse ...

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Isotropic 3D cardiac cine MRI allows efficient sparse segmentation strategies based on 3D surface reconstruction

Isotropic 3D cardiac cine MRI allows efficient sparse segmentation strategies based on 3D surface reconstruction

... from sparse arbitrarily oriented planes, the left ventricular cavity was reconstructed using an implicit B-spline surface reconstruction algorithm described in ...surface reconstruction technique was ...

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Sparse polynomial interpolation: sparse recovery, super resolution, or Prony?

Sparse polynomial interpolation: sparse recovery, super resolution, or Prony?

... the sparse polynomial is the unique optimal solution of a certain infinite-dimensional linear program on a space of measures, provided that a geometric condition of minimum spacing (between atoms of the support) ...

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Object-based 3D binary reconstruction from sparse projections in cone beam CT: Comparison of three projection operators

Object-based 3D binary reconstruction from sparse projections in cone beam CT: Comparison of three projection operators

... ABSTRACT We present herein a level set approach to the X-ray tomography problem with sparse projection data and study the impact of the pro- jection operator on the binary reconstruction accuracy and compu- ...

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Surface reconstruction from a sparse point cloud by enforcing visibility consistency and topology constraints

Surface reconstruction from a sparse point cloud by enforcing visibility consistency and topology constraints

... a sparse cloud of 3D points estimated from an image sequence: to avoid com- putationally expensive dense stereo, ...a sparse point ...a sparse point cloud reconstructed from videos, that are taken by ...

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Sparse sets

Sparse sets

... 7. Using sparse sets in error analysis Now several results about robustness may be reformulated in terms of sparse sets. Let us give an example from percolation theory. Consider a grid of vertical and ...

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Sparse stochastic bandits

Sparse stochastic bandits

... d in the minimax analysis. Since upper and lower bounds match, this is actually ineluctable. On the other hand, we aim at leveraging an additional assumption to reduce that (linear) dependency in d and even get rid of ...

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Constrained Sparse Texture Synthesis

Constrained Sparse Texture Synthesis

... Comparison. Our results are compared with 3 other decomposition-based tex- ture synthesis algorithms [ 7 , 12 , 11 ]. Peyr´e’s approach [ 11 ] is, to the best of our knowledge, the only synthesis model using ...

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Sparse k-means for mixed data via group-sparse clustering

Sparse k-means for mixed data via group-sparse clustering

... The present manuscript aims at proposing an explicit method for variable selection in a mixed-data framework, using a penalized criterion. Our contri- bution is two folded: first, we introduce a group-sparse ...

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Les Indo-européens et leur langue : reconstruction d’une reconstruction

Les Indo-européens et leur langue : reconstruction d’une reconstruction

... Alors que les travaux d’Émile Benveniste sur la morphologie des racines indo-européennes font autorité 49 , la syntaxe 50 est sans doute le maillon le plus faible des tentatives de reconstruction, en raison même ...

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Shallow sparse autoencoders versus sparse coding algorithms for image compression

Shallow sparse autoencoders versus sparse coding algorithms for image compression

... thierry.dumas@inria.fr, aline.roumy@inria.fr, christine.guillemot@inria.fr ABSTRACT This paper considers the problem of image compression with shallow sparse autoencoders. We use both a T-sparse autoen- ...

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