Sentence examples for feature task from inspiring English sources

The synthesis approach presented in this article provides the ability to apply any fitness measure found appropriate for the final feature task at hand (such as classification).

Implicit attitudes are generally operationally defined as mental representations that are unreported, inaccessible to consciousness, and detectable in paradigms such as the Implicit Association Test (Greenwald et al. 1998), the Affect Misattribution Procedure (Payne et al. 2005), the Sorted Paired Feature Task Bar-Annann et al. 2009) and the Go/No-Go Go/No-Go Association TaskNoseknand 2001).

Therefore, it is possible that the intensity of stimulation was not high enough to impair single feature task performance in this paradigm.

Previously, Chowdhury and DeAngelis [ 12] showed that generalized training from a feature task reduced the involvement of MT/V5 on a signal-in-noise task: reversible inactivation disrupted the monkey's perceptual judgments before, but not after, training.

This asymmetry was supported by an rANOVA with a significant interaction of session (pre versus post) and training task (feature-difference versus signal-in-noise) for the feature task (F1,31 = 6.60, p = 0.015), but not the signal-in-noise task (F1,31 = 2.52, p = 0.122).

That is, dual task activity in each region was less than the activity produced by the preferred single feature task and greater than the activity produced by the non-preferred task [1], indicating that the IFG and PC activity found in this paradigm does not scale with task difficulty.

This might explain why TMS in the current study selectively affected the conjunction task but not the single feature tasks.

Note that the dual task required WM manipulation of two features, whereas the single feature tasks only required one type of information to be manipulated.

Thus the role of domain-specific areas in conjunction tasks involving spatial and identity information, relative to their role in the respective single feature tasks, is not clear and is the purpose of the present study.

The co-occurrence of features task can be defined as finding the joint probability of multiple features occurred simultaneously.

On the other hand, VM fails for real-world scenes as the matched feature points task becomes a more challenging task.