REVIEW 2 cited by
Tomographic X-ray data of carved cheese
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
This is the documentation of the tomographic X-ray data of a carved cheese slice. Data are available at www.fips.fi/dataset.php, and can be freely used for scientific purposes with appropriate references to them, and to this document in http://arxiv.org/. The data set consists of (1) the X-ray sinogram of a single 2D slice of the cheese slice with three different resolutions and (2) the corresponding measurement matrices modeling the linear operation of the X-ray transform. Each of these sinograms was obtained from a measured 360-projection fan-beam sinogram by down-sampling and taking logarithms. The original (measured) sinogram is also provided in its original form and resolution.
Forward citations
Cited by 2 Pith papers
-
Randomized and Inner-product Free Krylov Methods for Large-scale Inverse Problems
New inner-product-free Krylov methods, sCMRH and sLSLU, combine Hessenberg basis construction with randomized sketch-and-solve to produce residual norms close to minimal residual methods.
-
Deep kernel learning for integral measurements
Deep kernel learning is extended to line-integral observations; a Hilbert space basis expansion turns the costly 2D integrals into 1D integrals, and neural-network pre-training stabilizes joint training.
Discussion (0). Continue with ORCID to comment.