Statistical learning of new visual feature combinations by infants
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Abstract
The ability of humans to recognize a nearly unlimited number of unique visual objects must be based on a robust and efficient learning mechanism that extracts complex visual features from the environment. To determine whether statistically optimal representations of scenes are formed during early development, we used a habituation paradigm with 9-month-old infants and found that, by mere observation of multielement scenes, they become sensitive to the underlying statistical structure of those scenes. After exposure to a large number of scenes, infants paid more attention not only to element pairs that cooccurred more often as embedded elements in the scenes than other pairs, but also to pairs that had higher…
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2Topics & keywords
Topics
Keywords
- Statistical learning
- Artificial intelligence
- Computer science
- Feature (linguistics)
- Associative property
- Pattern recognition (psychology)
- Predictability
- Coherence (philosophical gambling strategy)
UN Sustainable Development Goals
- Quality Education
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