M-tree [10] is the first balanced dynamic ball partitioning metric access method based on fixed-size disk pages.
Here, we proposed three different alternative distance metrics for comparing a brain image pair with increasing complexity, namely naïve pixel-wise distance metric, adjusted pixel-wise distance metric, and a method based on intensity summaries by histogram, row, and column (so-called HRC method).
Fig. 2 Procedures for AMA representation method based on metric tensor (mathbb {M}).
This method, based on Riemannian metric comparison, minimizes a cost function constructed from a measure of metric non-conformity that compares two metrics: the metric that transforms a given element into its reference element and a specified Riemannian metric that contains the desired target size and shape of each element.
In order to identify these repeats, we propose here a novel method based on a metric characterizing amino-acid properties (polarity, secondary structure, molecular volume, codon diversity, electric charge) using five previously derived numerical functions.
Also, an optimum method based on the performance metric has been designed to compare the performance of the heuristics developed.
An adaptive method based on the partition entropy metric, typically used in Information Theory, is employed for data discretization [ 24].
In this paper, we present an inpainting method based on sparse representations optimized with respect to a perceptual metric.
This paper presents an image inpainting method based on sparse representations optimized with respect to a perceptual metric.
In this paper, we have presented an inpainting method based on sparse representations optimized with respect to a perceptual metric.
