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Background subtraction is also used by many researchers but in complex situation, like hand over face, background cannot be segmented due to skin color similarities as reported in [24].
A box plot showing the number of probes with negative values following the background subtraction is also reported (Figure S2).
Background subtraction is also useful for modeling growth phenomena, since the background is non-biological and can contribute substantially (~25%) to the final spot intensity.
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Optimized probes were present on the arrays in triplicate; one set of standardized probes (Agilent Technologies, Palo Alto, CA) used for quality control and background subtraction was also present on the arrays.
The background term appears only if a background region is specified and background subtraction is done.
A 1σ uncertainty band, which comes from the background subtraction, is shown around zero.
An approach preferable to background subtraction is to model the background and data simultaneously.
A 1σ uncertainty band from the background subtraction is shown in orange around zero.
The background subtraction is done.
To detect moving objects, accurate background subtraction is essential.
Background subtraction is the first step to understand the scene.
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