Modeling visual attention via selective tuning
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The human attention mechanism can be categorized into two distinct classes: saliency-based attention and focused attention.
“The human attention mechanism can be categorized into two distinct classes (Tsotsos et al. 1995).”
From Large language models (LLMs): survey, technical frameworks, and future challenges (2024) · cites this paper as Tsotsos et al. 1995
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- Authors
- Tsotsos, J. K., Culhane, S. M., Kei Wai, W. Y., Lai, Y., Davis, N., & Nuflo, F.
- Affiliations
- University of Toronto (CA)
- ORCID
- Tsotsos, John K.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 1995-10
- Volume
- 78
- Issue
- 1-2
- Pages
- 507-545
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2089597841
- Cited by
- 1,143
- References
- 73
- Citations by year
- 2026: 12 · 2025: 41 · 2024: 28 · 2023: 32 · 2022: 36 · 2021: 25 · 2020: 29 · 2019: 39 · 2018: 42 · 2017: 32 · 2016: 41 · 2015: 46 · 2014: 40 · 2013: 63 · 2012: 57
- FWCI
- 12.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Artificial Intelligence (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- visual attention, winner-take-all, top-down control, hierarchical visual processing, attentional bias, image search, computational model of attention, primate vision, robot vision, machine vision
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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