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The clustering-based and the visual attention-based methods shared the temporal segmentation results with ours, but the latter one performed temporal segmentation once more on each video segment to get more and shorter segments so that one frame with the highest score could be selected in each segment.
The three methods shared the pretreatment before ultracentrifugation.
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The methods share the exact same first step.
Numerous researchers have attempted to solve this problem with mathematical programming or heuristic methods, but all these methods share the significant weakness of low computational efficiency.
Most of particle methods share the problem of high computational cost and in order to satisfy the demands of solvers, currently available hardware technologies must be fully exploited.
Both methods share the property that the phase boundaries are sharply computed in the sense that there are no numerical interior points for the description of a phase boundary.
However, both methods share the same general structure where a streaming step is followed by a collision step.
Both ESA and Hilbert-based methods share the use of a filterbank prior to AM-FM demodulation.
All of these methods share the property that they add special enrichment functions to a standard approximation space.
As shown in the figure, the three methods share the same template representatives that are selected from the original GMM-labeled templates.
Here, the run-time analysis is restricted to the run time of the dynamic programming part because all methods share the same tree-decomposition algorithm.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com