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In [9] the impact of distortion correction on the classification accuracy regarding celiac disease images has been investigated.
To study the impact of distortion on actual GWAS outcomes, we perform a simulation study with empirical patterns of LD.
To estimate the impact of distortion on the accuracy of the marker order on the genetic map, we compared the genetic position of each locus in the SY-PM genetic map with and without the inclusion of the distorted markers.
Due to the complex LD structure in the human genome, and also ascertainment effects from GWAS study designs, it is difficult to evaluate the impact of distortion on GWAS results analytically.
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Available at http://www.columbia.edu/~ap2231/ † "Measuring the impact of distortions in agricultural trade in partial and general equilibrium".
In such methods of global application, the mostly adopted approach is based on computing the impact of distortions on natural scene statistics of natural images.
The idea of the impact of distortions on NSS has been used in[104] for prediction of video quality where each frame of the video is decomposed into a Laplacian pyramid of a number of subbands.
A brief survey of NR methods of image quality assessment (IQA) based on the notion of quantifying the impact of distortions on natural scene statistics (NSS) is provided in[5].
The approach of estimating visual quality by quantifying the impact of distortions on natural scene statistics has gained a wide interest to gauge degradations due to different image processing techniques including compression.
Although these recent works on misallocation have provided valuable insights on the impact of distortions on how resources are allocated across firms, our understanding of the underlying factors driving the variation across countries in the firm size distribution remains somehow limited.
Also, in the domain of NR-P-based methods, there are many methods which work beyond simple artifacts computation and the quality assessment is derived from the impact of distortions upon NSS (referring to statistical characteristics commonly found in natural images).
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