The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Encoding Multielement Scenes: Statistical Learning of Visual Feature Hierarchies.
Abstract
The authors investigated how human adults encode and remember parts of multielement scenes composed of recursively embedded visual shape combinations. The authors found that shape combinations that are parts of larger configurations are less well remembered than shape combinations of the same kind that are not embedded. Combined with basic mechanisms of statistical learning, this embeddedness constraint enables the development of complex new features for acquiring internal representations efficiently without being computationally intractable. The resulting representations also encode parts and wholes by chunking the visual input into components according to the statistical coherence of their constituents. These results suggest that a bootstrapping approach of constrained statistical learning offers a unified framework for investigating the formation of different internal representations in pattern and scene perception.
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Citations
Cites
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“We propose that this is a statistical definition of chunking that is consistent with and complements the classical definition that is based on the functional limits of short-term memory (Chase & Simon, 1973; Ericsson, Chase, & Faloon, 1980).”
The Nature of Recollection and Familiarity: A Review of 30 Years of Research
Yonelinas, A. P. (2002) · Journal of Memory and Language · doi:10.1006/jmla.2002.2864 · Cited by 3,840
Neural Networks and the Bias/Variance Dilemma
Geman, S., Bienenstock, E., & Doursat, R. (1992) · Neural Computation · doi:10.1162/neco.1992.4.1.1 · Cited by 3,578 · cited 1×
“The only way to handle the curse of dimensionality is to reduce the size of the problem by decreasing the number of relevant dimensions within which new associations have to be learned ( Geman, Bienenstock, & Doursat, 1992 ).”
BackgroundBienenstock, E., Cooper, L., & Munro, P. (1982) · The Journal of Neuroscience · doi:10.1523/jneurosci.02-01-00032.1982 · Cited by 2,896
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Ericsson, K. A., Chase, W. G., & Faloon, S. (1980) · Science · doi:10.1126/science.7375930 · Cited by 579 · cited 1×
“We propose that this is a statistical definition of chunking that is consistent with and complements the classical definition that is based on the functional limits of short-term memory (Chase & Simon, 1973; Ericsson, Chase, & Faloon, 1980 ).”
A Specific and Enduring Improvement in Visual Motion Discrimination
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Cited by
The role of context in object recognition
Oliva, A., & Torralba, A. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.09.009 · Cited by 1,063
Implicit learning and statistical learning: one phenomenon, two approaches
Perruchet, P., & Pacton, S. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.03.006 · Cited by 830
Statistically optimal perception and learning: from behavior to neural representations
Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.003 · Cited by 672
Self-citationTurk-Browne, N. B., Scholl, B. J., Chun, M. M., & Johnson, M. K. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21131 · Cited by 523
Saffran, J. R., & Kirkham, N. Z. (2018) · Annual Review of Psychology · doi:10.1146/annurev-psych-122216-011805 · Cited by 426
Metadata
- Authors
- Fiser, J., & Aslin, R. N.
- Venue
- Journal of Experimental Psychology: General
- Published
- 2005
- Volume
- 134
- Issue
- 4
- Pages
- 521-537
- ISSN
- 0096-3445 (ISSN-L)
- 1939-2222
- OpenAlex
- W2116945498
- Cited by
- 209
- References
- 11
- FWCI
- 2.33
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
