From the Cover: Statistical learning of new visual feature combinations by infants

By József Fiser, Richard N. Aslin. 2002

506 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/ffaaa55557f63d417774026928d3855a8cd01d23

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Computer Vision and Pattern Recognition

In Experimental and Cognitive Psychology

Citations in the corpus

The surprising power of statistical learning: When fragment knowledge leads to false memories of unheard words (2009, background): “have been observed with other auditory and visual stimuli ( Fiser & Aslin, 2002; Saffran, Johnson, Aslin, & Newport, 1999; Turk-Browne, Junge, & Scholl, 2005), and with other mammals (Hauser, Newport, & Aslin, 2001; Toro & Trobalon, 2005).”
Bayesian models of object perception. (2003, background): “It is largely an open question of how the human visual system learns the appropriate statistical priors, but some priors as well as strategies for learning priors are likely to be rooted in our genes [28,29].”
The Goldilocks Effect: Human Infants Allocate Attention to Visual Sequences That Are Neither Too Simple Nor Too Complex (2012, background): “Infants are able to extract the statistical properties of their environment in a diverse array of learning tasks and domains, including sounds, words, people, shapes, and objects [6–11].”
Brain Mechanisms in Early Language Acquisition (2010, background): “Statistical learning has been shown in nonhuman animals (Hauser et al., 2001), and in humans for stimuli outside the realm of speech, operating for musical and visual patterns in the same way as speech (Fiser and Aslin, 2002; Kirkham et al., 2002; Saffran et al., 1999).”
Statistical Language Learning (2003, background): “For example, infants can track sequences of tones, discovering “tone-word boundaries” via statistical cues (e.g., Saffran, Johnson, Aslin, & Newport, 1999), and can learn statistically defined visual patterns (e.g., Fiser & Aslin, 2002; Kirkham, Slemmer, & Johnson, 2002); work in progress is extendi”
Object Individuation and Physical Reasoning in Infancy: An Integrative Account (2012, background): “Second, infants search for the conditions that map onto these outcomes until they detect a possible condition-outcome regularity (we assume that infants’ impressive statistical-learning ability plays a key role in this process; e.g., Fiser & Aslin, 2002; Saffran, 2009).”