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Attention is known to compensate for the finite neural capacity in visual information processing by selecting relevant information [ 1– 3].
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Selecting relevant information from the knowledge base shortens the decision-making time.
During writing, they reread the source texts multiple times to select relevant information.
But these standards define all project objects and do not give tools to select relevant information.
Visual attention allows us to select relevant information and ignore distractions.
In the first step, information from Twitter network is gathered and modeled in a graph by selecting relevant relations or patterns for the influence model.
Chemometrics uses mathematics and statistics to select relevant chemical information by analyzing chemical data, generating useful knowledge of a complex chemical system [ 38].
When processing a visual scene, there are mechanisms for selecting relevant and filtering out irrelevant information [ 33].
In biological vision systems, the attention mechanism is responsible for selecting the relevant information from the sensed field of view.
Attention plays a central role for selecting behaviorally relevant information among enormous retinal inputs.
Once there the data were imported by software, which selected the relevant information and drafted an article in everyday English.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com