Sentence examples for model for background from inspiring English sources

In Section 4, Method-1 is introduced with Gaussian mixture model for background and moving object detection.

Each detector has one model for background (learned using non-mine training signatures) and another for mine (learned using trained mine signatures).

In background modeling and motion detection module, they employ an adaptive model for background estimation applying mixture of Gaussians and appearance patterns, thereby presenting a stable and robust background model.

BATWING uses Markov chain Monte Carlo (MCMC) techniques to sample many reconstructed genealogies proportional to their probability under the coalescent model (for background see Wilson et al. [16]) in a Bayesian framework.

Without trying to perform an exhaustive study, we used the following parameters: motif length (m) = 10, number of different motifs to infer (z) = 2, expected number of sites in a given set of sequences (y) = 120, order of the Markov model for background probabilities (N) = 3.

The RMA convolution model for background correction of microarray data from Affymetrix platforms is very popular.

This method mainly includes three parts, namely detecting the moving regions approximately by calculating the inter-frames differences of symmetrical frames and counting the static index of each probable moving point; modeling for background by the statistics of brightness information and updating this model combining motion templates; then extracting moving objects and its edges.

This suggests that one possible approach to improve binding site prediction is to develop better motif (and background) models than the currently used position specific frequency model (PSFM) for binding sites and Markovian models for background.

When investigating the effects of traffic variables we also adjusted all models for background NO2 levels.

Both of these quantities are derived using the mixture cure survival model adjusted for background mortality [ 19].

Modern background subtraction algorithms operate by first building a model for the background.