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The problem of unmeasured states used in the control is also solved by reconstructing the missing states using flatness based interpolation.
This restriction can be overcome by reconstructing the missing images from the images acquired at consecutive observation sessions.
This fit provides a straightforward handle on several drawbacks of the technology: saturation (by reconstructing the missing signal beyond the saturation limit), overshining (by reconstructing the signal below the influenced feature) and spotting variability (by automatically adjusting the integration range to the source size).
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Compressive Sampling (CS) is an emerging technique to reduce volume acquisition time with minimal image degradation by sparsely sampling the object and reconstructing the missing data in software.
Richard Rastall, professor of historical musicology at the University of Leeds, spent 12 years reconstructing the missing part.
A SD reconstructs the missing samples by replicating the last decoded sample.
On the contrary, the PD reconstructs the missing samples by linear prediction (as in the CDE case).
In such situations, approaches are needed to help reconstruct the missing data.
This paper presents the use of a 3D morphing technique to reconstruct the missing inlay or crown occlusal surface.
Furthermore, by using the selected patches, we derive the representation model optimized for the target patch in terms of the SSIM index to reconstruct the missing area.
As described above, we can reconstruct the missing texture in the target patch.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com