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The background model is built as a mixture of Gaussians.
After the background model is built, a binarization image from the difference image is needed to show the target.
After the background model is built, we subtract the background model from the current frame and get a difference image.
The background model is built using four values: the mean, the standard deviation, the variation of the brightness, and chrominance distortion.
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Specific background models were built for each sequence type (upstream, first intron, 5'UTR, 3'UTR) by computing oligonucleotide and dyad frequencies in the whole set of genomics sequences of the same type.
The derivation procedure adopted here helps in understanding not only the model's limitations but also the conceptual background based on which the model is built.
A nonlinear model is built.
First, a basic reservoir model is built.
The model is built in MATLAB.
The program model is built modularly.
In the HMMTiling (HT) approach proposed by Li et al. (2005), a background probe model was built empirically using multiple data sets generated by a single lab.
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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