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Journal article

Top-down guidance of visual search: A computational account

Abstract:
We present a revised version of the Selective Attention for Identification Model (SAIM), using an initial feature detection process to code edge orientations. We show that the revised SAIM can simulate both efficient and inefficient human search, that it shows search asymmetries, and that top-down expectancies for targets play a major role in the model's selection. Predictions of the model for top-down effects are tested with human participants, and important similarities and dissimilarities are discussed. © 2006 Psychology Press Ltd.
Publication status:
Published

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Publisher copy:
10.1080/13506280500195482

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Institution:
University of Oxford
Department:
Oxford, MSD, Experimental Psychology
Role:
Author
Journal:
VISUAL COGNITION
Volume:
14
Issue:
4-8
Pages:
985-1005
Publication date:
2006-01-01
DOI:
EISSN:
1464-0716
ISSN:
1350-6285
URN:
uuid:847610d7-0bdc-4250-9520-ec4e2ba42ae9
Source identifiers:
311650
Local pid:
pubs:311650
Language:
English

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