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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found <t>in</t> <t>EMHMM.</t> Notes. a The representative hidden <t>Markov</t> model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI
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The Two Representative Patterns Found in EMHMM. Notes. a The representative hidden Markov model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI

Journal: Cognitive Research: Principles and Implications

Article Title: Impact of mask use on facial emotion recognition in individuals with subclinical social anxiety: an eye-tracking study

doi: 10.1186/s41235-025-00635-4

Figure Lengend Snippet: The Two Representative Patterns Found in EMHMM. Notes. a The representative hidden Markov model. The ellipses on the left show the ROIs as 2-D Gaussian emissions. The table on the right shows the priors (the probabilities that a fixation sequence starts from the ellipses) and the transition probabilities from one ROI to another in the sequence. b The actual assignment of fixations to each ROI

Article Snippet: The eye movement analysis with hidden Markov model (EMHMM) toolbox in MATLAB (Version 0.80) was used to analyze the eye movement data (Chuk et al., ; available at http://visal.cs.cityu.edu.hk/research/emhmm/ ).

Techniques: Sequencing