Sentence examples for material classification of from inspiring English sources

Figure 6 Material classification of a bare printed-circuit board.

Those previous methods were useful for material classification of printed circuit boards.

Next, we have applied the proposed method to material classification of a printed circuit board with various tiny elements.

As mentioned earlier, we elected to assess the performance of the proposed decorrelation technique (spectrum fuzzyfication) in the context of material classification.

Figure 4b depicts the ground truth of material classification by segmenting manually the image.

To fully evaluate the performance of the decorrelation methodologies analyzed in this investigation, the results shown in Table 1A, B will be complemented with the results achieved when the data decorrelation algorithms are evaluated in the context of material classification.

If the material classification is not available, geotechnical data of the material used in the construction of the embankment are needed.

The results obtained demonstrate the promising potential of ICAMM for material classification.

The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification.

In order to evaluate the efficiency of the proposed technique, in this section we compare its performance against those attained by different decorrelation schemes in the context of non-ferrous material classification.

Hence, they might be adequate for material classification but they allow no fundamental understanding of the material properties' origins.