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  1. CRISP: A computational model of fixation durations in scene viewing.Antje Nuthmann, Tim J. Smith, Ralf Engbert & John M. Henderson - 2010 - Psychological Review 117 (2):382-405.
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  • SWIFT: A Dynamical Model of Saccade Generation During Reading.Ralf Engbert, Antje Nuthmann, Eike M. Richter & Reinhold Kliegl - 2005 - Psychological Review 112 (4):777-813.
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  • The e-z reader model of eye-movement control in reading: Comparisons to other models.Erik D. Reichle, Keith Rayner & Alexander Pollatsek - 2003 - Behavioral and Brain Sciences 26 (4):445-476.
    The E-Z Reader model (Reichle et al. 1998; 1999) provides a theoretical framework for understanding how word identification, visual processing, attention, and oculomotor control jointly determine when and where the eyes move during reading. In this article, we first review what is known about eye movements during reading. Then we provide an updated version of the model (E-Z Reader 7) and describe how it accounts for basic findings about eye movement control in reading. We then review several alternative models of (...)
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  • Interactions dominate the dynamics of visual cognition.Damian G. Stephen & Daniel Mirman - 2010 - Cognition 115 (1):154-165.
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  • Computational Modelling of Visual Attention.Laurent Itti & Christof Koch - 2001 - Nature Reviews Neuroscience 2 (3):194–203.
    Five important trends have emerged from recent work on computational models of focal visual attention that emphasize the bottom-up, image-based control of attentional deployment. First, the perceptual saliency of stimuli critically depends on the surrounding context. Second, a unique 'saliency map' that topographically encodes for stimulus conspicuity over the visual scene has proved to be an efficient and plausible bottom-up control strategy. Third, inhibition of return, the process by which the currently attended location is prevented from being attended again, is (...)
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