Sentence examples for feature thresholds from inspiring English sources

The feature thresholds and optimized moving window size were based upon steady-state no-fault tests and startup transient tests.

Even more importantly, the calculation of these positive predictive values does not take into account the fact that, through the interolog detection, our initial predictions (before application of genomic feature thresholds) are already enriched for true interactions.

Due to the limited number of image features and the simplicity of feature thresholding strategy, the diagnostic power of PET/CT might not have been fully explored.

From each heterologous genome, the top BLAST hit to each array feature (threshold e-value 10-14) was used to obtain the percent similarity between the two sequences and the length of the alignment.

Through this combination of genomic features, thresholds may be decreased while maintaining an acceptable number of false positives (see Additional file 1 for an estimation of the false positive rates).

Input:, is the training image and is the class label, is the weight,     is the number of co-occurred features; Output: ; Initialize:   ; (1) Retrieve the calculated CoLBP feature vectors, ; (2) Use decision stump to find all features threshold values and parity values ; for   do.

Detailed studies have shown that parts of these networks can act as modules with distinct dynamical features (threshold, hysteresis, oscillatory instability, switch-like instability, and so on) [ 15].

(b_1 le 150) and (b_2 le 250) ("SIFT feature matching"), Thresholds for the area of feature region (S_s) and (S_l) ("Landmark selection procedure") were set to 2500 and 40,000, respectively.

In-line filtering, such as support or feature count thresholds, can be used to extend the practical range.

Specifically, neither global nor local feature detection thresholds showed any dependence on cue colour.

The key parts include the extraction of conditional probabilistic distributions from "travel pre-estimate" questions, the probabilistic distributions from importance sorting questions for "user anxiety" features and the probabilistic distributions of features' psychological thresholds for "user anxiety" questions.