The area-of-interest problem in eyetracking research: A noise-robust solution for face and sparse stimuli.
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Noise-robust fixation detection in eye movement data: Identification by two-means clustering (I2MC).Differences in Looking at Own- and Other-Race Faces Are Subtle and Analysis-Dependent: An Account of Discrepant Reports.What to expect from your remote eye-tracker when participants are unrestrained.The disengagement of visual attention in the gap paradigm across adolescence.Learning Spoken Words via the Ears and Eyes: Evidence from 30-Month-Old Children.Is human classification by experienced untrained observers a gold standard in fixation detection?Operationalizing atypical gaze in toddlers with autism spectrum disorders: a cohesion-based approach.An Examination of Recording Accuracy and Precision From Eye Tracking Data From Toddlerhood to Adulthood.A Validation of Automatically-Generated Areas-of-Interest in Videos of a Face for Eye-Tracking Research
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The area-of-interest problem in eyetracking research: A noise-robust solution for face and sparse stimuli.
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2015 nî lūn-bûn
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2015年学术文章
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name
The area-of-interest problem i ...... n for face and sparse stimuli.
@en
The area-of-interest problem i ...... n for face and sparse stimuli.
@nl
type
label
The area-of-interest problem i ...... n for face and sparse stimuli.
@en
The area-of-interest problem i ...... n for face and sparse stimuli.
@nl
prefLabel
The area-of-interest problem i ...... n for face and sparse stimuli.
@en
The area-of-interest problem i ...... n for face and sparse stimuli.
@nl
P2860
P1476
The area-of-interest problem i ...... n for face and sparse stimuli.
@en
P2093
Ignace T C Hooge
Roy S Hessels
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P2888
P304
P356
10.3758/S13428-015-0676-Y
P577
2015-11-12T00:00:00Z
P5875
P6179
1025077692