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It can be observed that SSIM-based method outperforms specially in the texture region which confirms that the proposed denoising scheme preserves the structures better and therefore has better perceptual image quality.
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In the first scenario, our method outperforms an existing topology-aware method particularly for complex inputs and higher genus constraints.
In addition, our method outperforms previous molecular methods aimed at determining only dreissenid DNA presence4,28,29.
Analysis of simulation data showed that this method outperforms existing methods.
Experimental results indicate that our proposed method outperforms previous methods.
Results show that the proposed method outperforms its counterparts.
This new method outperforms previous works [18].
That is, the proposed method outperforms the reference methods.
Our method outperforms the original functional parcellation in intra-network cohesion and both methods in motor network identification.
Table 8 shows that HBE method outperforms other classifiers using all validation methods.
Therefore, the network-based method outperforms the hybrid-property based method.
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