Taylor R. Hayes, PhD
Taylor R. Hayes, PhD
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Searching for meaning: Local scene semantics guide attention during natural visual search in scenes
Scene inversion reveals distinct patterns of attention to semantically interpreted and uninterpreted features
Look at what I can do: Object affordances guide visual attention while speakers describe potential actions
Meaning maps detect the removal of local semantic scene content but deep saliency models do not
Rapid extraction of the spatial distribution of physical saliency and semantic informativeness from natural scenes in the human brain
Meaning and expected surfaces combine to guide attention during visual search in scenes
Deep saliency models learn low-, mid-, and high-level features to predict scene attention
Linking patterns of infant eye movements to a neural network model of the ventral stream using representational similarity analysis
Looking for Semantic Similarity: What a Vector Space Model of Semantics Can Tell Us About Attention in Real-world Scenes
Meaning maps capture the density of local semantic features in scenes: A reply to Pedziwiatr, Kümmerer, Wallis, Bethge & Teufel (2021)
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