Sentence examples for perfect identification from inspiring English sources

Exact(18)

Winnie, played with wide-eyed spunkiness by Ms. Bledel (a star of television's "Gilmore Girls"), is a perfect identification figure, energetic and attractive but just vague enough to allow young viewers to pour their own identities into her.

First, it suggests that a much smaller number of stimulus trials is needed for perfect identification.

In order to launch a strain on the market its perfect identification at the species and strain levels is needed.

Experimental results both on a home-brewed activity data set and the public Schüldt's data set show the perfect identification performance and high robustness of the system.

It is also noted that RI-FJLT hashing still consistently achieves almost perfect identification accuracy under rotation attacks even with large rotation degrees.

Our preliminary study [19] on a small database showed that FJLT hashing provides nearly perfect identification accuracy for the standard test images such as Baboon, Lena, and Peppers.

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Similar(42)

This view appears to be supported by the results from the artificial datasets, which showed near-perfect identification of known subgroups but one instance of a subgroup being split into 'daughter' subgroups.

PhpSSRMiner provides a user-friendly interface which integrates its back-end pipeline to streamline the process of perfect SSR identification by SSRIT [ 22], imperfect SSR identification by Sputnik [ 23], PCR primer design using Primer3 [ 24] and in silico amplification of the designed primers via IsPCR [ 25].

Although DNA fingerprinting cannot empirically produce a perfect positive identification, the probability of error a false positive can be decreased to a point that it seems nonexistent.

The results of the cross-validation step showed that, although perfect individual identification was not achieved, the rate of success was greatly above chance (32% versus 6%).

Following the above equation: a low value of recall would indicate a more conservative estimate which is unable to capture many of the existing connections; a low value of precision will indicate prediction of incorrect connections not appearing in the actual network; and a value of 1 will indicate perfect network identification.

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