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We validate our framework using the benchmarked PETS 2006 video surveillance dataset and our own sequences, and achieve a mean recognition F-Score of 0.82.
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Statistically significant correlations were found between mean CRP 2 f-score and SCT 2, mean total combined CRP score and mean combined SCT score, and between combined CRP mean f-score and combined SCT score.
The alternative hypothesis is that kDDN has the greater mean of F-score.
The highest mean F-score was used as a metric for selecting the most appropriate values.
A two-tailed t-test was conducted by hypothesizing the mean F-score obtained by the proposed NSGWO method at significance level = 0.05.
The whole procedure was repeated m times, and we calculated the mean F-score, absolute error, and accuracy.
where f(w) is the recognition score of the word w, μ(w) is the mean recognition score of all instances of the word w in the corpus, and σ(w) is the standard deviation of all instances of the word w in the corpus.
Globally, the mean recognition score in first position RR(1), calculated over the entire gesture corpus is of 67.3%.
Globally, the mean recognition scores in first position RR(1), respectively calculated over the iconic gestures and metaphoric gestures subsets, are of 88.6 and 75.2%.
These mean corrected recognition scores are shown for each group in Table 1.
The mean NRS-F score was 3.8 ± 2.5, with 57.6% of respondents experiencing moderate to high levels of fatigue.
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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