Different from existing graphic saliency detection methods, which estimate saliency based on pixel-level contrast, the proposed method detects salient objects by computing object-level contrast.
In the field of texture reconstruction, not only the methods based on the texture synthesis but also many methods, which estimate missing intensities by utilizing statistical features of known textures within a target image as training patterns, have been proposed.
Comparing with traditional uncalibrated methods, which estimate online the hand-eye relationship characterized by varying image Jacobian, the uncertainty of image Jacobian is eliminated via DOB to approach a given nominal model in this paper.
In absence of a family-based genetic information, a valid alternative to the experimental approach is provided by computational methods which estimate, by means of specific criteria, haplotypes from the set of genotypes extracted from a population of individuals.
Tests for selection were performed using four methods which estimate selection in a phylogenetic context available in the Datamonkey web interface [ 36].
Although some very sophisticated Bayesian species tree estimation methods, such as *BEAST [ 11], have been developed, for computational reasons only summary methods (which estimate species trees by combining estimated gene trees) have become widely used in phylogenomics.
Better than other methods which estimate the remodeling status detecting humeral biomarkers, it may provide site-specific information directly by measuring MAR and BFR at different time points using the fluorochrome sequential labeling approach [ 15].
However, the ultimate, still not-achieved aim of these physical approaches has been to provide scientists with feasible calibration methods which estimate absolute specific target concentrations in the presence of a complex non-specific background from fluorescence intensity data.
Moreover, we used three different temporal methods, which estimate N e from genetic change between two or more sampling points (for reviews of N e estimation, see e.g. [ 2, 55].
It is worth noting that volumetric breast density methods which estimate breast density from two-dimensional (2D) mammography, such as the one used in this work, do not directly measure the "true" volume of the dense fibroglandular tissue in the breast but rather a surrogate estimate based on imaging physics and validated assumptions of the breast anatomy [ 47].
