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The experimental results indicate that the proposed method achieves significant performance improvement.
In both strategies the method achieves significant reduction of the computational cost compared to conventional Markov chain Monte Carlo methods.
The proposed method achieves significant performance improvement in presence of narrow-band noise when clubbed with missing feature theory based score computation scheme.
Experimental results of QNLK show that the proposed method achieves significant objective coding gain and visual quality improvement, compared with both H.264/AVC high profile and HEVC.
Experimental results show that our method achieves significant improvement in age classification when compared to the existing approaches and other popular classifiers.
Experimental results on both the English PDTB and Chinese CDTB data sets show that our proposed method achieves significant improvements over baselines using SynData.
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The results of isolated word speech recognition experiments showed that this method achieved significant improvements over conventional cepstral mean normalization (CMN) in a reverberant environment.
The proposed method achieved significant improvement of classification accuracy as compared with the RWPE method for each data length.
The main reasons why the above discussed methods achieve significant performances in efficient use of network resources are either in the fact that, during a sampling interval, only a subset of the sensors measures the field by means of RS or in the fact that CS acquisition is actually realized jointly with the routing procedure.
The method achieves a significant increase in accuracy of 8.1% when compared to the baseline method, resulting in an arteriole/venule classification accuracy of 86.97% (per pixel basis) over the entire retinal image.
The proposed method achieves a significant throughput improvement compared with the conventional method because it efficiently eliminates the collision from hidden node.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com