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Experimental results show that the proposed method outperforms related works in terms of preserving the quality of the restored image.
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Comparisons show that the proposed algorithm significantly outperforms related methods.
Empirical evaluation on several datasets shows that MoRFpred outperforms related methods: α-MoRF-Pred that predicts α-MoRFs and ANCHOR which finds disordered regions that become ordered when bound to a globular partner.
While the new method was able to outperform related work, the analysis revealed that the performance for exposed residues was considerably lower than for buried ones.
We have trained and tested the classifier on various datasets and shown that it outperformed related methods.
The results show that our method can be used to design a satisfactory NN ensemble and outperform related works.
Therefore, it is clear from the experiments that our proposed method outperforms global traditional descriptors, previous local texture descriptors based on LBP and previous related works.
The experimental results suggest that the proposed method outperforms opponent methods in terms of controller effort, measures associated with transient response and criteria related to steady-state.
The PageRank-based method outperforms degree centrality-based method for identifying disease-related genes from WTSN.
This new method outperforms previous works [18].
That is, the proposed method outperforms the reference methods.
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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.
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CEO of Professional Science Editing for Scientists @ prosciediting.com