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Fig. 6 Results on accuracy of attention prediction.
All those factors influenced efficiency of attention prediction for different subjects.
The success of building a person-independent attention prediction model was validated by testing attention prediction on the dataset of 18 persons with moderate accuracy of up to 0.753, comparable to the state-of-the-art studies in the field.
Depth frames with resolution 512 by 424 pixels were recorded but were not used for attention prediction.
The comparison of attention prediction accuracy of seven classifiers is done on a data set comprising 18 subjects.
As we aimed to build a generalized attention prediction model applicable to various persons, we have encountered observable differences in the behavior of the test persons.
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We will discuss these attentional interpretations in Section Studies on the relation between auditory attention and prediction, where interactions between prediction and attention mechanisms will be considered.
Section Studies on the relation between auditory attention and prediction has provided evidence that prediction and attention interact in various ways.
And if guidance is pre-attentive and feature combination requires attention, the prediction would be that conducting a conjunctive search is a serial process with respect to spatial attention and feature-based attention, and thus inefficient.
For example, the basal ganglia may be involved in more implicit, or automatic, predictions of regularity rather than task-based attention to prediction, whereas the explicit task may induce participants to rely on motor representations or imagery with premotor cortex activation.
As we will see, this will diverge considerably from what has been considered as attention or prediction in the previous literature as summarized in Section Prediction and attention have often been confused in previous research.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com