Your English writing platform
Discover LudwigSuggestions(1)
Exact(10)
Table 6 contains the mean ((bar{X})) and the standard deviation (s) of the performance for each evaluated algorithm after the computation of the subjective evaluation results.
After the simulation scenario, we evaluated algorithm performances.
We evaluated algorithm performance in Darfur, Sudan for the 2004 calendar year.
We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow.
We evaluated algorithm performance in boreal forests of Central Siberia, Mediterranean-type ecosystems of California, and sagebrush steppe of the Great Basin region of the US.
Because of the diversity of potential outputs from the LTS data, we evaluated algorithm performance against summary metrics for disturbance, recovery, and stability, both for capture of events and longer-duration processes.
Similar(50)
Fig. 7 Speech/non-speech hit rates of the evaluated algorithms under different SNR levels.
Open image in new window Fig. 12 Means plot and Tukey confidence intervals (CI) for the evaluated algorithms.
Table 9 allows a visual comparison to be made of the evaluated algorithms when processing noise-corrupted input images.
Among the evaluated algorithms, OFLO shows the best performance, but at the same time it requires the highest computational complexity.
For example, several studies evaluated algorithms using functional similarity as a proxy for orthology [24], [25], whereas others evaluated algorithms against sets of orthologs identified by phylogenetic analysis [10], [25].
Write better and faster with AI suggestions while staying true to your unique style.
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