Modelling Visual Search with the Selective Attention for Identification Model (VS-SAIM): A Novel Explanation for Visual Search Asymmetries

Cognitive Computation

Volumn 3, Issue 1, 2011, Pages 185-205

  Heinke, Dietmar ^a   Backhaus, Andreas ^b  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b FRAUNHOFER INSTITUTE FOR FACTORY OPERATION AND AUTOMATION IFF   (Germany)

Author keywords

Computational modelling; Search asymmetry; Visual attention; Visual search

Indexed keywords

CLASSICAL RECEPTIVE FIELD; COMPUTATIONAL MODELLING; EMPIRICAL EVIDENCE; HUMAN ABILITIES; IN-LINE; LARGE PARTS; MULTIPLE OBJECTS; NOVEL CONCEPT; OBJECT IDENTIFICATION; RECEPTIVE FIELDS; SEARCH ASYMMETRY; SEARCH PERFORMANCE; SELECTION STAGES; SELECTIVE ATTENTION FOR IDENTIFICATION MODELS; SIMPLE LINES; SIMULATION RESULT; TOPDOWN; TRANSLATION INVARIANTS; VISUAL ATTENTION; VISUAL SEARCH;

KNOWLEDGE BASED SYSTEMS;

BRAIN MODELS;

EID: 79952818576     PISSN: 18669956     EISSN: 18669964     Source Type: Journal    
DOI: 10.1007/s12559-010-9076-x     Document Type: Article

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