Sentence examples for automatic algorithms and from inspiring English sources

In this section, we compare the detection results from GraFIX (both the automatic algorithms and the hand-coding) with those from previous algorithms.

Finally, we compared hand-coding results with GraFIX automatic algorithms and previous automatic detection algorithms (the velocity-based algorithms from Wass et al., 2013; the adaptive velocity-based algorithms from Nyström & Holmqvist, 2010; and the I-VT filter velocity-based algorithm as implemented in Tobii-studio 3.0.0).

Furthermore, the similarity in results between our automatic algorithm and manual initialization suggests that the detection issues are due to ASM itself.

Multiple sequence alignments were generated with MAFFT v7.017, using the FFT-NS-ix2 algorithm and the BLOSUM62 scoring matrix for protein alignment and the automatic algorithm and the 200PAM/k=2 scoring matrix for nucleotide alignment (Geneious Pro software).

Briefly, visceral compartments were delineated and then an automatic algorithm and a Hounsfield threshold value of -50 to -150 was used to determine the cross-sectional fat content within that area (cm).

The SMART-AV trial found no differences in HF-related events and LVESV between systematic AVD optimization with an automatic algorithm and AVD optimization using echocardiography or a fixed AVD of 120 ms. The reasons why our results differ remain speculative.

The objective of this paper is to present and apply automatic algorithms to evaluate and improve non-stationary outdoor thermal comfort in urban areas.

Human performance at categorizing natural visual images surpasses automatic algorithms, but how and when this function arises and develops remain unanswered.

For that reason the use of automatic algorithms was limited and most structures were created under visual control.

We proposed original automatic algorithms for processing approach and retraction force curves of FVI's.

*Statistically significant Figure 4 is an illustrative example of the cone identification results, where the middle row shows the mean cone identification performance for both automatic algorithms, while the top and bottom rows show the performance approximately one standard deviation above and below the mean.