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Background subtraction assuming a given percent of genomic DNA contamination (pctBkg) was performed as follows.
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As shown in Figure 1B and 1C, background subtraction assuming 0.5% or 1% gDNA contamination led to relatively modest decreases in ORF and ncRNA coverage but to significant drops in coverage of IGR and AS positions.
Traditional background subtraction algorithms assume the camera is static and are based on simple per-pixel models of scene appearance.
The background subtraction used here assumes that the camera platform is not moving.
The data were analyzed including background subtraction, using a LOWESS (locally weighted regression) method on the background-subtracted data.
Owing to the variable nature of the radiation incident on the scintillator, background subtraction is a multistep process.
Background subtraction is a crucial step in the preprocessing of Raman spectrum.
In real environments, due to complex and various background types, background subtraction is a challenging task.
Curve fitting was performed after Shirley background subtraction using a Lorentzian-Gaussian fitting.
Our background subtraction algorithm is a variant on common background subtraction techniques (e.g. see M. Piccardi, Background subtraction techniques: a review. Systems, man and cybernetics, 2004 IEEE international conference, Vol. 4. IEEE, 2004).
Background subtraction is a simple method of target object separation from an input image using a background image.
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