Sentence examples for subtle classification from inspiring English sources

Exact(2)

In addition VAA users tend to avoid taking 'extreme' positions in the Likert scale; as a result differences between 'Completely Agree' and 'Agree' and 'Completely Disagree' and 'Disagree' create noise rather than more subtle classification.

Although our current technique is built on simple set-based classification, there is clearly scope to develop statistical models which allow for a more subtle classification procedure.

Similar(58)

It was the Stoics who systematically developed a logic of propositions and devised subtle classifications of predicates.

These results also demonstrated subtle deficits in classification speed and accuracy in a category search task.

Meanwhile, the COG/KOG result was also affected by the subtle difference in functional classification to function similar proteins, especially transporters.

There were no other interactions involving the status of left inferior frontal gyrus, suggesting that both groups and modalities contributed to these effects of lesion location (although this analysis lacks statistical power to detect a subtle interaction with aphasia classification).

These approaches allow for a multidimensional semantic space where concept features can vary in importance, evolve or change dynamically, accounting for many possible classifications and subtle variations of concept meaning, including the new and the less plausible ones.

Texture features are the intrinsic properties of image and provide an efficient image classification to detect subtle alterations in the gray level distribution of an image [27].

Furthermore, by learning classification models from subtle image features, it may be possible to distinguish between different Parkinsonian syndrome subtypes, such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) from (I123 FP-CIT data.

Successful fine-grained image classification methods learn subtle details between visually similar (sub- classes, but the problem becomesub- classestly more challenging if the details are missing due to low resolution.

However, a data-driven optimal exposure classification may reveal subtle changes in an exposure pattern, for instance due to an intervention, that will be left undetected by conventional methods [ 42].

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