The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Saliency, attention, and visual search: An information theoretic approach
Open accessAbstract
A proposal for saliency computation within the visual cortex is put forth based on the premise that localized saliency computation serves to maximize information sampled from one's environment. The model is built entirely on computational constraints but nevertheless results in an architecture with cells and connectivity reminiscent of that appearing in the visual cortex. It is demonstrated that a variety of visual search behaviors appear as emergent properties of the model and therefore basic principles of coding and information transmission. Experimental results demonstrate greater efficacy in predicting fixation patterns across two different data sets as compared with competing models.
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Cites
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Cited by
Attention, uncertainty, and free-energy
Feldman, H., & Friston, K. J. (2010) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2010.00215 · Cited by 1,365
Eye guidance in natural vision: reinterpreting salience
Tatler, B. W., Hayhoe, M. M., Land, M. F., & Ballard, D. H. (2011) · Journal of Vision · doi:10.1167/11.5.5 · Cited by 775
Active inference and epistemic value
Friston, K., Rigoli, F., Ognibene, D., Mathys, C., Fitzgerald, T., & Pezzulo, G. (2015) · Cognitive Neuroscience · doi:10.1080/17588928.2015.1020053 · Cited by 731
Jiang, M., Huang, S., Duan, J., & Zhao, Q. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298710 · Cited by 729
Metadata
- Authors
- Bruce, N. D. B., & Tsotsos, J. K.
- Venue
- Journal of Vision
- Published
- 2009-03-01
- Volume
- 9
- Issue
- 3
- Pages
- 5-5
- ISSN
- 1534-7362 (ISSN-L)
- OpenAlex
- W2103666701
- Cited by
- 855
- References
- 74
- FWCI
- 68.16
- Type
- journal article
- Language
- en
- Open access
- gold
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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.