Sentence examples for maximum likelihood template from inspiring English sources

In order to reduce computation and storage complexities, we also propose two methods for template selection: minimum distance template selection (MDTS) and maximum likelihood template selection (MLTS).

In maximum likelihood template selection, each frame of a cluster center s* as generated by the MDTS method is relabeled by a set of GMMs that are selected by using a maximum likelihood criterion, so as to make the representative better characterize the templates in each cluster.

For maximum likelihood template selection (MLTS), we use the DTW described in Section 3.2 to align the templates in a cluster C i to the MDTS-initialized template center s*. Figure 4 illustrates an outcome of aligning the sequences s1,…, s N to s* in C i, where the frames x t 1 1, …, x t N N of the sequences s1,…, s N, respectively, are aligned to the frame x t * * of the cluster center s*.

To further reduce the costs of memory space and computation, we propose template selection methods to generate template representatives based on the criteria of minimum distance (MDTS) and maximum likelihood (MLTS) and we also propose a template compression method to integrate information from training templates to obtain more informative template representatives.

Maximum likelihood estimation using SSH and GFRKD rhodopsin templates suggested that the temperate reef fishes have multiple retinal pigments (Fig. 5).

A probabilistic estimator, e.g., maximum likelihood estimator, is typically applied for the comparisons to the possible key templates where the largest value is said to be the targeted key.

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