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To evaluate the computational complexity of the proposed LV-ET, we compute the average time consumption per video for both trajectory extraction and descriptor representation on UCF sports.
Next we compute the average BER for Θ = 1 conditioned on {Ω1, Ω2, Ω3}.
For all results, we compute the average MSE by taking 200 realizations of the estimated channels.
For each simulation setting, we compute the average of 10 runs.
We compute the average in (19) by means of the classic GQR's suggested in [22].
First, we compute the average dissimilarities among the pixels in several clusters of different sizes, by using different window sizes.
Next, to achieve (20), we compute the average value of all the variances, as (text {MMSE}_{text {ext}}^{S}).
In this case starting from the estimates given by (21) and (22), we compute the average values (23).
To address this incompatibility, we compute the average of the weights within one column of the support window.
Based on this value, we compute the average value (Q) of all the elements in each fracture.
We compute the average distances within the groups and evaluate their relationship and ability to capture the evolutionary closeness of organisms.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com