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The experimental tests, conducted using five HDR images and four local TMOs, show that the visual quality of images marked with the μ-law-based approach, evaluated by means of the peak signal-to-noise ratio (PSNR) computed over tone-mapped images, is better than the one associated with the method relying on bilateral filtering.
Next, we applied a computational method (Splitter [ 12]) using an approach evaluated by Johnson and colleagues [ 13] to identify genomic regions showing enrichment of TR binding.
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The sensitivity of our in silico SNP detection approach was evaluated by comparison of validated SNPs detected using in vitro approach, selection of the most sensitive SNP detection tool and 96 SNPs validation.
In this paper, the performance of this approach is evaluated by comparing it with the performance of other, established approaches to optimal experimental design for model discrimination.
The proposed approach is evaluated by precision, recall, F1 and time performance, and meanwhile the appropriate thresholds for the algorithms in our approach are determined through experiments.
Our approach is evaluated by multi-subject tests.
The effectiveness of the proposed approach is evaluated by simulations.
The performance of each approach is evaluated by calculating the average hypervolume value over 51 runs.
The proposed approach is evaluated by a real HJ-1A hyperspectral data at Bohai Sea.
The proposed approach is evaluated by system level LTE networks simulator developed in c++.
The performance of our approach was evaluated by using experiments of through-wall human detection.
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