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Average search time was recorded as a function of chromaticity, position, and length of the search commands.
The resulting model was then used to choose color assignments for all the elements of the display that would result in the fastest average search time for the display and search tasks.
b Average search time.
Figure 5 shows the recognition rate and average search time.
Fig. 3 Recognition rate and average search time on the LFW. a Recognition rate.
The recognition rate and average search time are shown in Fig. 3.
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Average search times varied widely because of the variations in target contrast and overall was faster on the fatty images.
Figure 2 shows the recognition rates and average search times of the proposed method 1000 subjects for the gallery when the BDH parameters changed.
Fig. 6 Average search times for detecting targets on the original or sharpened mammogram images, after adapting to the original images or sharpened images.
Specifically, the average search times were more often faster for the sharpened images after adapting to the original images (16/19 times, p = 0.004) or vice versa (15/19 times, p = 0.019).
Repeated best-first search was from 700 to 2500 times slower with average searching times ranging from two to six hours.
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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