Cited by 1,143Visual Attention and Saliency DetectionVisual perception and processing mechanismsAdvanced Vision and Imaging

Modeling visual attention via selective tuning

Open access
Tsotsos, John K., Culhane, Scan M., Kei Wai, Winky Yan, Lai, Yuzhong, Davis, Neal, Nuflo, Fernando·1995·Artificial Intelligence

Integrity signals

Registry

Crossref · 10.1016/0004-3702(95)00025-9

Cites

73 of 73 references verified0 citation errors · 0 not checkable

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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)
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
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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