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The method performed very well in various target detection methods and achieved good detection results on different data sets such as PASCSAL VOC benchmarks and INRIA Person.
An overview of available knowledge and up-to date progress in application of active aerodynamic control is provided, starting from concepts, methods and achieved results in aerospace and helicopter research.
The sensitivity of the AuNP/GONR hybrid electrode was examined through chronoamperometry and linear sweep voltammetry methods, and achieved a linear range from 0.5 μM to 10 mM, covering the normal glucose level in human blood.
We compared our tool with published state-of-the-art methods and achieved better performance.
We developed a target gene prediction approach that combines three widely used prediction methods and achieved a sufficiently high prediction accuracy.
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The performance of phishGILLNET3 is better than all the other competing methods and achieves an F-measure of 100%.
By using this architecture, we overcome the drawbacks of previously proposed methods and achieve better recognition accuracy.
Comparisons with other countries with different cultures, dependent on studies using different methodologies and sampling methods and achieving lower participation rates, may not be of primary interest here.
Rigorous evaluation of the classification accuracies shows that the ANN outperforms the other methods and achieves ≈90% accuracy on test data.
Experimental results show that our method outperforms the state-of-the-art methods and achieves the good performance on the visual saliency detection task.
The results indicate that the proposed approach outperforms the most recently reported five methods and achieves 0.64 20.90% improvement on average accuracy.
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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