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We introduce a novel similarity metric (correlation of gradient orientations (CGO)) for disparity estimation and carry out a comparative performance assessment with respect to the state-of-the-art metrics.
These genes were then organized based on the gene ontology annotations for angiogensis, cell proliferation and chemotaxis using dChip (distance metric: correlation, linkage method: average).
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Correlations were calculated as (metric) Pearson correlation coefficients.
Correlations were determined as metric (Pearson) correlation coefficients.
All local local and regional regional pollutant pairs showed moderate-to-strong positive correlations for each metric; however, correlations for regional regional pollutant pairs tended to be lower.
In this way, we achieve a quality index that is comparably as computationally efficient as typical NR metrics and as accurate as the FR algorithm Video Quality Metric (97% correlation).
Four chaotic invariants, which include the largest Lyapunov exponent, metric entropy, correlation dimension and mutual information, of all pressure signals are computed.
Therefore, four image quality assessment metric and correlation functions will be adopted in the payoff function for encoder player.
The input for the SOTA analysis was: Metric: Pearson correlation, max.
We then computed the maximum linkage disequilibrium (LD) value, on the basis of the r metric (Pearson correlation squared), among all SNP pairs within each pair of windows.
Clustering was performed using custom made R functions using adapted script with following characteristics: heatmap function, metric: Pearson correlation, aggregation method: average.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com