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The proposed landmark-aided approach obtains the smallest mean and standard deviation values of absolute heading estimation error.
The results show that the evolutive approach obtains the best results in the context of the real data from a riparian area in southern Spain.
The results of the extensive experiments on recovering pattern instances from nine open source software systems demonstrate that our approach obtains the balanced high precision and recall.
Firstly, this approach obtains the positions of candidate points by detecting the local maxima of a series of energy maps constructed by Gabor filter responses.
Moreover, the experiments on the real SAR images show that our approach obtains the regions with labeling consistency and preserves the edges and details at the same time.
The approach obtains the flame response to acoustic excitation using Large Eddy Simulations (LES), and couples this with a low-order wave-based network representation for the acoustic waves within the combustor.
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The results demonstrate that our approach obtain the better profit than other five approaches.
They observed that the hybrid approach obtained the best results, although the number of extracted candidate terms was median.
However, our ensemble-based approach obtained the best performance in terms of all the three measures.
As the structural information used in this paper indicate the nature of hot spots, our approach obtained the highest recall in hot spot prediction.
Generally, the different approaches obtain the same classification from better to worse in terms of OPS as in terms of qGlobal (PEASS metrics are within a 0 to 100 interval, being 100 the best result).
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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.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com