Sentence examples for amount parameter from inspiring English sources

If is the SGBNR-processed pixel value corresponding to an original pixel value and is the "Amount" parameter, then the resulting pixel value is given by (3).

In addition to the variability of parameters due to divergent kinetics between clinical cases, there is a lesser amount parameter variability for each case, a.k.a., within case variability.

The main drawback of the SCNR is that it can introduce a magenta cast to the sky background, which must be controlled by a careful dosage of the Amount parameter.

The filtering intensity is driven by the filter size, the "Amount" parameter, which fixes the percentage of the original pixel value to be preserved, and the "Edges Protection Threshold", which evaluates the "edgeness" degree of each pixel (also depending on the luminance level) and modulates the filter strength consequently.

In each alignment mode m, where m ∈ { R O, R U, U O, U U}, we ran Algorithm 4, setting the input parameter dataset to all the structures from over the RNAStrand [ 50] database (containing 1751 RNA structures), and setting the number of iterations (the amount parameter, in the code below) to 2 × 10.

After all, the variation of rotor size and air amount parameters with the capacity of the classification process was investigated.

DOE allows to separate the most important influencing factors on the targeted cutting process, to clarify their interaction, to reduce the overall amount of parameter sets that need to be examined and to identify the optimized parameter regions, respectively.

Particularly, DNNs involve very flexible and compact structures: they usually consist of a large amount of parameters, and the parameters are highly shared among feature dimensions and task targets (phones or states).

Finally, some methods aim to reduce the amount of parameter learning to avoid overfitting, achieved by regularisation techniques modifying the training objective function or limiting the parameter learning cycles (Duda et al, 2001).

Within each run, the maximum amount each parameter can change decreases after each iteration.

Sometimes just a small amount of parameter tuning can save weeks of processing and yield very good classification results.