Sentence examples for performance of the methods with from inspiring English sources

Further tests have been performed to assess the performance of the methods with different measurement types and configurations.

We illustrate the performance of the methods with examples of four different data sets.

However, the stronger performance of the methods with learned parameter(s) suggests a small performance gain can be realized from the added effort of tuning a query to each data set.

In order to evaluate the performance of the methods with respect to chemotypes, we generated a clustering on the basis of the chemical similarity between the molecules of each subset.

The GOP size for QCIF videos was set to 4 and that for CIF videos was set to 8. In addition to the two methods with continuous modulation levels (FBeD (CNT), MLO (CNT)), the performance of the methods with discrete modulation levels (as discussed in Section 3.7) is also shown in Figure 17.

Although promising results have been achieved by BM3D when denoising flat and textures scene images at high noise levels σ>10, the performance of BM3D decreases when denoising images have a lot of fine details regions at σ≤10; see the results of Barbara and House images in Table 2. Figure 11 shows the performance of the methods with various levels of noise on each of the four images.

The numerical performances of the methods with discrete sources are illustrated through simulations in spheroidal and cylindrical particle cases.

We illustrate the performance of the method with several numerical examples.

Nevertheless, our proposed usage of textural features, particularly the BSIF-TOP, still surpasses the performance of the method with deep object features when iDT is the base feature.

First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics.

The final bar depicts the performance of the method with all filters applied.