Sentence examples for worsening accuracy from inspiring English sources

The new procedure was applied on three different marble samples and outcomes are encouraging, but further testing is running to better understand to what extent sample size can be reduced without worsening accuracy of results, taking into account that stone is a very heterogeneous material.

In this context, a classifier requires to provide high accuracy of the defect class without severely worsening the accuracy of the non-defect class.

Combining (r)ϕθ with ∇I improves robustness but at the same time, worsens accuracy.

The prolonged treatment delivery time required for IMRT and HT relative to three-dimensional conformal radiotherapy may worsen the accuracy of treatment because of increased intra-fractional patient motion.

Of the two who started matched within ± 5% of Adjuvant! before the oncology visit, one of them became mismatched, but 6 of the 18 who started mismatched moved into agreement with Adjuvant!, for a net total of 7 accurate patient estimates after the visit (p = 0.125, McNemar's test, based on the 6 of 7 who improved rather than worsened in accuracy).

Alternative but unlikely explanations for the progressive discrepancy include that the researcher setting arm elevation with the universal goniometer systematically worsened in accuracy as the elevation angle increased, or that the SMA's accelerometer itself introduced a systematic error as it rotated around its longitudinal axis.

Palming the ball will cause a slower release time, which worsens your accuracy and speed.

Motion estimation is facing a dilemma of reducing the computational complexity at the cost of worsening the estimation accuracy.

L-Glutamic acid, glycine, and GABA were quantified as o-phthalaldehyde (OPA) adducts modifying the method proposed by Lehtonen [ 27] in order to notably reduce the time of separation to only 2.7 minutes but without worsening selectivity and accuracy.

The results in this paper demonstrate that both image- and reconstruction-based PVC can be applied to improve SUV accuracy without worsening test-retest variability.

The proposed MSE provides the MFCC with around 1% accuracy improvement for Test Sets A and B (additive-noise environments), but it still worsens the recognition accuracy for Test Set C (with both additive noise and channel distortion).