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The target visual output will be got from these selected sub-clusters.
We define an objective function based on mean square error (MSE) measure between estimated and target visual parameters.
This method is based off using asymmetric, non-linear transformations learned in kernel space to map the target visual domain to the source.
A strong method for testing these effects, we argue, is to make object category and target visual features orthogonal in stimulus design.
Finally, a visual environment for a target visual language can be automatically generated by exploiting a YACC-like tool based on XPG.
No significant differences between deaf and hearing individuals were found in target visual and auditory areas when the motion and form components of the stimuli were isolated (contrasted with a static visual image).
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Traditional single-target visual search tasks do not reveal these development-based differences in attentional abilities.
Critically, this difference between adult and children's performance is not captured by single-target visual search tasks.
Importantly, such feature/conjunction differences between adults and children are not seen in more traditional single-target visual search tasks.
Single-target visual search (Wolfe, 1998) has long been among the main methods for assessing visual attention.
Single-target visual search has been used to investigate the development of attention (e.g. Donnelly et al., 2007; Merrill & Conners, 2013; Merrill & Lookadoo, 2004; Taylor, Chevalier, & Lobaugh, 2003; Trick & Enns, 1998; Woods et al., 2013).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com