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The proposed method demonstrates better performance than conventional optimization methods, which brings benefits to both basis pursuit and orthogonal matching pursuit.
The second image with complex background, comparing with the vector-valued C-V model, our method demonstrates better in visual perception.
When compared with the state-of-the-art prediction models in the two benchmark datasets, our method demonstrates better performance.
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The CMS-HCC method demonstrated better performance relative to the Charlson and Elixhauser methods in predicting in-hospital and six-month mortality.
In all these cases, our proposed method demonstrated better performance than the original version of mm-tSNE, as measured by the neighbourhood preservation ratio.
On the other hand, in the case of very high SNR, such as that above 15 dB, although the proposed method consistently demonstrates better performance, the performance becomes competitive with respect to the other methods in comparison.
It does so by providing a more reliable method of its measurement that demonstrates better validity particularly in relation to serious adverse outcomes when compared to a widely known frailty index.
In comparison with other similar methods, this two-step procedure demonstrates better performance overall.
This method has demonstrated better performance than the conventional Gaussian mixture model (GMM -based method [6] in VC experiments usinGMM -basedded speech data.
We hypothesized that this method would demonstrate better sensitivity and specificity than are currently achievable with conventional PCR.
In off-line comparisons, our method demonstrated significantly better accuracy compared to the Kalman filter, the Wiener filter, and the population vector method [10], [13].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com