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The original HDR-VDP metric [10] was the first metric designed for HDR content.
The user selection criterion is based on an adaptive, utility-based scheduling metric designed for the purpose.
The results of our two methods (BClus and CAMNEP) and BotHunter were compared using a methodology and a novel error metric designed for botnet detections methods.
It aims to improve the performance of the superpixel earth mover's distance (SP-EMD), a recently proposed distance metric designed for depth-based hand gesture recognition.
In order to quantitate CN noise, we adapted a QC metric designed for microarray data, the median absolute pairwise difference (MAPD) algorithm (Affymetrix, 2008).
To address this challenge, we separately use two measures of population density: (i) percentage of the population residing in an "urban" area; and (ii) a novel metric designed for this analysis, which we denote as a country's "density score".
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This chapter examines some of the implications of Metric Design for the design process.
The metric was designed for quality assessment of HDR video content, but can also be used for HDR still images.
This metric is designed for applications requiring a fairly coarse time resolution, placing more importance into finding the correct events within the block than finding their exact location.
Note that the PATH-DR metric was originally designed for a one-to-many routing protocol.
This result is consistent with that expected theoretically, since the metric is specifically designed for this purpose.
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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